Edge computing and AI Imaging

Edge computing and AI Imaging

In today’s rapidly advancing technological environment, AI imaging and edge computing are reshaping the capabilities of industries from mining and manufacturing to urban planning.

Edge Computing and AI Imaging

In the digital tapestry of today’s world, two technologies—AI imaging and edge computing—stitch new patterns of possibility across the canvases of industry and urban management. These innovations aren’t just enhancing systems; they’re transforming them, pushing the boundaries of what’s possible in real-time responsiveness and analytical precision.

Questions we will address in this article

  1. How does edge computing enhance real-time data processing in critical industrial environments?

  2. What are the advantages of AI imaging in monitoring and analyzing complex data across various sectors?

  3. How does SAPHI ensure the ethical deployment of these technologies, particularly concerning data privacy and security?

The Quiet Revolution of Edge Computing

Imagine a technology so astute it processes information where it’s collected, slashing response times to mere milliseconds and preserving bandwidth. This isn’t a page from science fiction—it’s the reality of edge computing. By decentralizing data processing, edge computing brings lightning-fast insights to the most remote corners of a mine, the busiest intersections of a city, and the fastest-moving parts on a production line. In these critical environments, where each second counts, edge computing isn’t just useful; it’s transformative.

AI Imaging: Seeing Beyond the Human Eye

Now, picture a world where cameras and sensors do more than record—they analyze and interpret. AI imaging delves deep into the visual data, identifying patterns unseen by the human eye. From detecting minute defects on a bustling factory floor to analyzing traffic flow in a sprawling metropolis, AI imaging offers a clarity that is precise and unprejudiced. It’s not about replacing the human gaze but augmenting it, providing a set of insights that are comprehensive and actionable.

AI Computer Vision

Navigating the Ethical Waters

As we chart these technological waters, the twin beacons of security and ethics guide us. The deployment of AI imaging and edge computing brings with it a profound responsibility: to protect the data integrity and uphold the privacy of individuals. Innovators and regulators alike must collaborate to ensure these technologies enhance lives without encroaching on liberties—a delicate balance of benefit against bias.

SAPHI employs edge processing to enhance the security of AI imaging applications in several key ways:

  • Data Localization: By processing data directly at the source, SAPHI minimizes the need to transmit sensitive information over networks, reducing the exposure to potential breaches.
  • Real-Time Processing: Edge processing facilitates real-time data analysis, allowing for immediate action without the lag of cloud processing. This speed not only improves efficiency but also prevents data accumulation, reducing the risk of unauthorized access.
  • Compliance and Control: With edge processing, SAPHI ensures that data handling complies with stringent regulatory requirements for privacy and security. This localized control over data also allows for customizable privacy protections tailored to specific operational environments and jurisdictions.
AI computer vision

Examples of it in Action​

At SAPHI, we’ve been at the forefront of harnessing AI imaging and edge computing to address specific challenges in mining, manufacturing, and smart cities. Each of these sectors presents unique demands, and our approach has been to tailor solutions that not only resolve current needs but also anticipate future challenges.


In the mining industry, the combination of AI imaging and edge computing has revolutionized safety protocols. SAPHI are leveraging these technologies to monitor critical infrastructure and equipment deep within mines. By analyzing data on-site, these systems:

  • Predict equipment failures
  • Detect structural weaknesses
  • Support pre-emptive corrections
  • Monitor PPE and safe behaviour compliance
  • Monitor vehicle health (harsh breaking, collisions, rolling etc.)
  • Monitoring operator safety (fatigue, seatbelt compliance, phone usage etc.)

This proactive approach to safety marks a significant departure from traditional reactive models, offering a future where potential hazards are systematically identified and mitigated.


On the manufacturing floor, precision and efficiency are paramount. SAPHI leverages AI imaging to ensure that every component meets quality standards through real-time monitoring. With edge computing, these insights are processed directly at the manufacturing site, enabling:

  • Failed iron detection
  • Automated quality control
  • Reduction of waste and improvement of line efficiency

This integration of technology streamlines production processes, ensuring high-quality output and reduced operational costs.

Urban Planning

In urban environments, SAPHI’s application of AI imaging and edge computing transforms city management by enhancing efficiency and safety. These technologies are adept at:

  • Assessing road utilization
  • Pedestrian flow analysis
  • Boat movement and jetty utilization
  • Event data

Such smart city solutions facilitate more livable, safe, and efficiently managed urban areas, proving essential in the drive towards sustainable urban development.

The Future is Now

This narrative of transformation is already being woven into the very fabric of our industries and cities by pioneering solutions like Shellshock AI. These technologies are not mere tools; they are partners in our ongoing quest to build smarter, safer, and more sustainable environments.

In this era of rapid technological advancement, the role of innovators is not just to adapt to changes but to lead them, ensuring that as our capabilities expand, they do so with consideration for both the individual and the collective. As we stand on this brink of technological evolution, let us embrace these tools with wisdom and wield them with care.

Thank you for reading!

To find out more about Shellshock AI follow us on LinkedIn here, and reach out to our team here contact@saphi.com.au

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Partnering with nbn®

Partnering with nbn®

We are thrilled to announce our partnership with nbn® New Developments, joining forces to address the unique and evolving needs of developers. This collaboration with nbn® Smart Solutions marks a significant step for Saphi as a tech-agnostic solution provider. Together, we’re committed to tackling urban heat challenges and enhancing the value of developments through advanced AI technologies.

smart city solutions

The Evolution of Smart Solutions

Our partnership with nbn was a natural fit, founded on a shared commitment to transforming urban landscapes into intelligent, sustainable ecosystems. This strategic alliance aligns closely with our core values and vision, providing us with a solid platform to harness nbn® Networks extensive capabilities. Through this collaboration, we’re empowered to deliver versatile, tech-agnostic urban solutions that significantly elevate the value and functionality of both developments and cities, paving the way for smarter, more connected communities.

The World's First Microclimate Control Project

A prime example of our innovative approach is the SIMPaCT (smart irrigation management for parks and; cool towns) project, currently operational in Sydney Olympic Park.

This initiative was designed with a clear objective: to combat urban heat and reduce water consumption. We achieved this by deploying 250 smart sensors across the park for critical data collation overlayed with two advanced artificial intelligence algorithms, all backed by the robust infrastructure of the nbn network.

This intricate system works by optimising the existing irrigation network, which in harmony with the greenspaces of bicentennial park reduces the suburb’s temperature by up to 4 degrees while also achieving an impressive 15% annual saving in water usage. It’s a tangible demonstration of how smart technology can create a more liveable, sustainable urban environment.

Smart City Solutions

What Developers of The Future Will Adopt

As we look to the future, the role of innovative technologies like our AI imaging technologies in urban development will become increasingly pivotal. For developers, the value of these AI imaging solutions is clear and multifaceted, and they are available now.

For example, SAPHI’s AI imaging solution ‘Shellshock AI’ (see here: Shellshock AI Making Developments More Valuable) affords developers the ability to gather precise insights into critical metrics such as the number of cars passing by their display villages, foot traffic in their stores, loitering times and the duration of each visit. These metrics offer deep insights into the appeal and value of various units, shops, and public spaces, translating into hard, actionable data on footfall patterns and space utilization.

Our partnership with nbn has been instrumental in scaling these solutions. It gives us the platform to expand our support and offerings without compromising our core values. This means our clients benefit from the best possible technology at a more accessible cost, backed by the reliability and redundancy of the nbn network.

Thank you for reading!

SAPHI is a tech-agnostic solution provider, committed to delivering innovative solutions that leverage the latest technology to help our clients achieve their goals.

Our team of experts is dedicated to providing the best service to our clients, and we are always available to answer any questions you may have about IoT and its role in your business.

Contact us anytime to learn more about how SAPHI can help you achieve your priorities through technology.

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What is Green IoT?

What is Green IoT?

Green IoT, or “green” Internet of Things, is a rapidly growing field that combines the power of IoT technology with sustainable and environmentally-friendly practices. But how does green IoT work?


Green IoT

In this article, we explore the concept of Green IoT, including its definition, how it differs from traditional IoT, and its role in the Energy Transition and Net Zero movement. We also examine examples of green technology, the technical aspects of Green IoT, and the importance of Green IoT for both the environment and the economy.

Questions we will address in this article

  1. What is Green IoT?
  2. How does Green IoT work?
  3. What are some examples of Green IoT in action?
  4. Why is it so important?
  5. Can IoT really be eco-friendly?

A Growing Area of IoT

As we continue to advance technologically, it’s crucial that we also consider the environmental impact of our innovations.

Enter Green IoT, or sustainable IoT, which aims to reduce the ecological footprint of the internet of things while improving resource management and efficiency.

With the world facing immense pressure to address climate change, the integration of IoT technology with sustainable practices has become essential for both individuals and organizations. By utilizing renewable energy sources, reducing energy consumption, and designing for easy recycling, Green IoT can play a major role in creating a more sustainable future.

Green IoT and wind turbines

What is Green IoT?

Also known as sustainable IoT, it is the marriage of internet of things technology and environmentally friendly practices. It aims to minimize the ecological impact of technology while enhancing resource management and efficiency.

Traditional vs Green

Traditional IoT primarily focuses on connecting devices and collecting data, neglecting the environmental impact of the technology. Green IoT, on the other hand, incorporates sustainable practices into the design and implementation of IoT systems. This includes utilizing renewable energy sources, reducing energy consumption, and designing devices for easy recycling.

How does it relate to the Energy Transition & Net Zero?

It is closely tied to the Energy Transition and achieving Net Zero emissions. As the world shifts away from fossil fuels towards renewable energy, Green IoT enables monitoring and optimizing energy consumption in buildings, industrial processes, and transportation. 

Achieving Net Zero, or balancing emissions produced with those removed from the atmosphere, can be assisted by reducing energy consumption and waste through IoT, as well as improving resource management efficiency.

How Does Green IoT Work?

The technical aspects of Green IoT involve the integration of IoT devices and sensors with renewable energy systems, energy storage systems, and energy management systems. These systems are connected to the internet, allowing for real-time monitoring, analysis, and control of energy usage.

How does Green IoT work with AI?

Artificial Intelligence (AI) plays a significant role in sustainable IoT. AI-based algorithms can analyze the data collected from IoT devices and sensors to identify patterns and make predictions. This can help optimize resource usage and improve energy efficiency. For example, AI algorithms can predict when energy demand will be high and adjust production accordingly, reducing the need for fossil fuel-based power generation.

AI computer vision

How does Green IoT work with Automation?

Green IoT has the potential to improve resource management and reduce waste through the use of automation and real-time monitoring. IoT sensors can be used to monitor and control the performance of industrial processes, reducing emissions and waste. Smart home systems can also be used to monitor and control energy usage in residential settings, reducing energy consumption and costs. Additionally, it can also be used to monitor and optimize the performance of renewable energy systems, such as solar panels and wind turbines, to maximize energy generation and reduce the need for fossil fuel-based power.

Green IoT is not just about reducing energy consumption but also about using it more efficiently, this is where Industry 4.0 comes in, it leverages the power of IoT, Big Data, AI, and Robotics to optimize the production processes and reduce waste. With this integration, the industry can become more efficient and sustainable.

Robotics automation

Examples of it in Action

Green IoT is not just a concept, it is already being implemented in various industries to create sustainable and efficient solutions. From smart cities to agriculture, Green IoT is making a real impact on the environment and economy. Let’s take a look at some specific examples of it in action:

Smart Building Automation – IoT sensors and controls are used to optimize heating, ventilation, and air conditioning systems in commercial buildings to reduce energy consumption and improve indoor air quality.

Smart Grid Management – IoT-enabled devices and systems are used to monitor and control energy consumption in real-time, allowing utilities to balance supply and demand to reduce energy waste and improve overall efficiency.

Remote Monitoring of Renewable Energy Sources – IoT sensors and cameras are used to monitor and maintain solar panels, wind turbines, and other renewable energy sources, helping to ensure optimal performance and reduce downtime.

Smart Transportation – IoT-enabled sensors and cameras are used to monitor traffic patterns, optimize traffic flow, and reduce emissions from vehicles.

Precision Agriculture – IoT-enabled sensors and cameras are used to monitor crop growth, soil moisture, and weather conditions, helping farmers to optimize crop yields and reduce water usage.

Why Green IoT is Important?

Climate Change

Climate change is one of the most pressing issues facing our world today. Green IoT plays an important role in addressing this issue by reducing greenhouse gas emissions and other pollutants. Additionally, it can help to promote the use of renewable energy sources, such as solar and wind power, which can help to reduce dependence on fossil fuels and mitigate the impacts of climate change.


It can also improve economic efficiency by reducing energy costs and increasing the use of resources in a sustainable way. For example, Green IoT can be used to optimize energy usage in buildings, reducing energy bills and increasing the value of the building. Additionally, Green IoT can be used to optimize the performance of renewable energy systems, such as solar panels and wind turbines, to maximize energy generation and reduce the need for fossil fuel-based power.

Can IoT really be 'Green'?

Traditional IoT

Traditional IoT often relies on the use of non-renewable energy sources and can contribute to environmental degradation through the generation of electronic waste. The proliferation of connected devices also increases the demand for raw materials and contributes to the depletion of natural resources.

Green IoT

Green IoT, on the other hand, is designed to minimize the environmental impact of IoT by using renewable energy sources, reducing energy consumption, and increasing resource efficiency. It can also enable the use of smart technologies to optimize resource management, such as reducing waste and increasing recycling.

smart city solutions

Potential for IoT to support sustainability in the future

With the integration of technologies such as AI, Big Data, and Industry 4.0, IoT has the potential to support sustainability in the future by enabling more efficient and sustainable production processes, reducing resource consumption, and supporting the transition to a circular economy. 

Additionally, IoT can also support the transition to a low-carbon economy by providing real-time monitoring and control of energy consumption, reducing the need for fossil fuel-based power and enabling the integration of more renewable energy sources into the grid.

Key Take Aways

In summary, Green IoT is a new approach to IoT that focuses on creating sustainable and environmentally friendly solutions. It differs from traditional IoT in its focus on energy transition and net zero, and it uses technologies such as automation, robotics, and AI to improve resource management and reduce waste. 

The importance of sustainable IoT lies in its ability to not only benefit the environment but also improve economic efficiency and address climate change. Additionally, it addresses concerns about the environmental impact of traditional IoT and has the potential to support sustainability in the future.

Thank you for reading!

SAPHI is a tech-agnostic solution provider, committed to delivering innovative solutions that leverage the latest technology to help our clients achieve their goals.

Our team of experts is dedicated to providing the best service to our clients, and we are always available to answer any questions you may have about IoT and its role in your business.

Contact us anytime to learn more about how SAPHI can help you achieve your priorities through technology.

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What is IoT?

What is IoT?

A child’s toy, your car, streetlights and even your coffee machine! There isn’t much out there that doesn’t fall under the umbrella of IoT in one form or another. But, with its unbridled influence, the inevitable question for many of us arises “what is IoT?”.

Electronics Solutions

What is IoT?

IoT has long been touted as the way of the future but what does it mean and how does it work? If we were to take a shortcut and consult the google gods, as most of us do, you would be presented with this:

“The Internet of things describes physical objects that are embedded with sensors, processing ability, software, and other technologies that connect and exchange data with other devices and systems over the Internet or other communications networks…”

– overly complex google definition

And, like many google definitions, we find ourselves looking like this corgi. More confused than when we started.

In this article, we will break down this unnecessarily complex topic into plain English and provide you with real-life examples of its utilisation in our daily lives.

What you will get from this article

  1. What is IoT?
  2. How does it work?
  3. Why IoT is so popular?
  4. Examples of its use in industry

What is IoT - Explained simply

For a more concise definition, I asked our director and computer engineer Cameron for his response:

“IoT refers to all of the physical devices out there that are connected to the internet.”

– Cameron | Director SAPHI

IoT encompasses just about anything with electronic components – the smartwatch on your wrist, the phone in your pocket, and the TV in your living room are all things that can be connected to the internet. Hence the name Internet of Things. But at SAPHI, we like to refer to these things as ‘Ground-to-Cloud devices‘.

What do you mean by 'Ground-to-Cloud'?

We can conceptualise IoT devices as those things that capture data from the real world (the ground) and make it available to users anywhere, globally, via some medium (the cloud).

Aside from just collecting and transmitting data, Ground-to-Cloud devices can be customised to manipulate their environment based on that shared data. For example, using the right equipment, we could trigger a mining vehicle to stop when a technician or another vehicle is detected within its exclusion zone. It goes without saying what value this would provide in terms of safety.

How Hot Is IoT Right Now?

As of this writing, it is prolific. In 2021, the number of IoT devices globally surpassed 12.3 BILLION! And it is not showing any signs of slowing down, with estimates predicting this number to explode to more than 27 billion by 2030!

Why is IoT so popular?

There is no single reason. It comes down to a multitude of factors. However, a key driver of its proliferation is its ability to facilitate sweeping improvements cross-industry. You may have heard that “Data is the new gold”, and right now, we are experiencing a gold rush of global proportions, and we have only just scratched the surface in terms of its potential. 

IoT facilitates data-based decision making, providing managers with the raw facts required to make sensible business decisions that will have an impact.

So, it is as simple as buying some sensors and plugging them in?

Unfortunately, no. 

There is a bit of effort required in setting up an effective IoT network that will provide you with actionable information. IoT devices are, at their very core, blank slates of potential. They require the right configurations, deployment conditions and management to produce consistent results.  

Beware The Claims of IoT Companies

You cannot have an industry boom without encountering your fair share of snake oil salespeople, and this goes doubly for the world of IoT. A quick google search of IoT devices will throw you millions of results, all claiming to be the be-all and end-all. The problem is that these devices are rife with inflated claims of capability. Put simply; the real-world results don’t match the claims on the box. 

Don't be deterred though!

The fact that there exist poor quality IoT products in a world where everyone is trying to make a quick buck should come as no surprise, but with a few nifty tips and tricks, you can quickly learn to sift through the noise and find the right fit for you. You can find these tips in our previous blog post, ‘What to consider when choosing a sensor‘.

Is IoT Worth It?

Well, that depends. IoT can be either a bringer of joy or stress. It depends on your use case, sensor selection and technical capabilities on-hand to oversee its deployment.

When done right, IoT has a multitude of benefits that can see improvements in process efficiencies, safety and the bottom line. Below are just a few of the most common benefits we see when deploying networks for our clients.

Improved Asset Utilisation

Relatively inexpensive integrated IoT systems can provide your management team with tangible insights into the organisation’s heartbeat. We can garner insights into the downtime of machinery, their performance, health, frequency of use, etc.

With your finger on the pulse of your assets, it becomes easy to make informed data-based decisions that improve workplace efficiency and view their impact in real-time.

Improved Labour Utilisation

If assets are the heartbeat, your staff are the veins and arteries keeping everything alive and moving. With some unique smarts integrated into existing business practices, we can accurately monitor the flow of activities within the organisation to identify bottlenecks.

Are our forklift operators struggling to find pallets? Do our trucking fleets take the most efficient routes to clients? Are parts and systems remaining idle for too long? 

In parallel with asset tracking, these insights provide holistic insights into the overall efficiency of your company. With the guesswork removed, your team will have the data required to improve practices and keep your competitors at bay.

Predictive Maintenance

By integrating proven industrial machine learning systems into your machinery, your team will receive notifications of impending errors days in advance, giving you plenty of time to address issues before they become catastrophes. 

Having spent a lifetime working with large scale mining machinery and manufacturers, we understand all too well that when assets are down, money is burning. This is why we have invested heavily in procuring, assessing and integrating the most advanced machine learning systems from around the world to give our industrial client’s the benefits of bleeding-edge technology to maximise labour and asset utilisation. 

Strategic Advantage

The most successful companies in the world are the ones with the most actionable data in-front of them for continuously improving practices, products, and systems. With the implementation of targeted IoT initiatives (we can help to develop these), the strategic conversations move away from “What should we do?” to “This is what we need to do to improve”.

Key Take Aways

IoT is not a panacea in and of itself; it requires key use case development, vetted systems and a dedicated team to deploy and manage it for long-term success. Whilst this sounds like a lot of effort, the advantages provided for many industries greatly outweigh the investment. 

Furthermore, you don’t have to do it yourself! We have a team of expert engineers available to guide your journey into this space to ensure investment is maximised and outcomes are plentiful. 

Thank you for reading!

Thank you for reading this article. We hope it gave you some valuable insights into IoT.

Need support?

To see if your team can benefit from the implementation of IoT systems, reach out to our experienced engineers at contact@saphi.com.au for a quick chat. 

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What is Machine Learning? Explained With Dogs

What is Machine Learning? Explained With Dogs

Machine learning is a prolific buzzword that appears to be ever-growing in popularity, especially over the past decade. However, for such a touted topic, few have set out to break it down into plain language. In this post, we will be doing just that. So, what exactly is machine learning?

What is machine learning

Is machine learning worth it?

Having worked for the past decade in the world of technology development, we regularly come across people who associate machine learning with superior outcomes.

But is this really true?

Yes and no… It is most certainly not as useful as many people would have you believe and is most certainly not suited to every application. However, machine learning can be immensely helpful for some specific use cases.

But what are the use cases of machine learning, and how does it work? We will explore this and more in the following sections.

What you will get from this article

  1. What is machine learning?
  2. How does it work?
  3. Real-life use case example

What is machine learning?

At a high level, machine learning is nothing more than the science behind making computers learn with minimal human input. That is, setting them up so they can learn from experience and improve themselves over time without being made to do so.

Machine learning however is not as complex as the media would have you believe, nor is not even as innovative! Machine learning has been around since the 50’s. 

How can this be?

Because machine learning is nothing more than a basic algorithm running through a loop, constantly returning to a fork in logic of “yes” and “no”. Either “yes”, the guess was right so associate it with the input, or “no”, do not associate this answer with the input.

How does it know if it is right or wrong?

In crude terms, we need something to provide feedback to the algorithm. This segways nicely into our next section.

How does machine learning work?

Before we dive in, I should preface the following by first clarifying that this is a reductionist interpretation of just one method that a machine learning algorithm may be trained.

Let's use an analogy

Let’s suppose you are crazy about dogs and are fervently studying for an exam on dog breeds. For this exam, you will be presented with a picture of a dog (such as SAPHI’s office mascot seen below) and then asked what the breed is.

What is machine learning?

So now we know what the exam will be and the skills we require to ace it, we can set about making a plan to prepare ourselves. In this case, our plan is pretty straightforward; we expose ourselves to hundreds of pictures of dogs and have someone provide us with basic feedback on our answers. Slowly but surely, we learn to recognise not just differences between vastly different species such as a Great Dane and a Chihuahua. 

Sounds too easy, right?

Well, it is a little more complex. Whilst we must learn to recognise differences between breeds, we must also learn to recognise the variations within each breed. 

What do I mean by this?

Let me answer this question with another. What makes a Jack Russell a Jack Russell? The variation within this one breed can be significant and even resemble the characteristics of another, leading to confusion.

For instance, some Jack Russells will have longer fur, shorter fur, long legs, short legs, many spots, few spots, floppy ears, straight ears, but when it comes down to genetics; they are all the same breed.

What is machine learning?

Through repetition and consistent feedback, we slowly learn to spot the variations, so we don’t confuse them with similar-looking breeds in the future.

What does this have to do with machine learning?

Bear with me; it will all tie together. Let’s say you are studying for the exam with your friend, Bec. Bec collects 20 different pictures of various breeds and begins quizzing you. These pictures are your ‘inputs‘, and the answers you give are your ‘outputs‘ – just like in the world of machine learning.

You look at image one (input one) and give your three best guesses (outputs) in order of probability.

You are 60% confident the breed is a Jack Russell. However, a nagging suspicion makes you think it could be a Fox Terrier or possibly even a Scottish Terrier.

1. Jack Russell

How does machine learning work?

2. Fox Terrier

3. Scottish Terrier

What is machine learning

After you guess, Bec reveals the answer is, in fact, number 2, the Fox Terrier. With this feedback on hand, you store that image in memory, so when it reappears in the future, you will have a higher probability of picking the correct breed.

Through a process of repeated trial and error, you eventually build up an ever-improving, segmented mental map of each breed and its variations. In other words, you become a super-efficient dog-breed detector.

So, is this how machine learning works?

In a round-a-bout way, yes. Crudely speaking, machine learning learns similarly to humans through repetition and feedback. 

Right now, machine learning is being deployed by companies across industries to solve some pretty large scale technical problems. One such company is found right here in Australia.

Case study

Tiliter is a Sydney based company that has raised millions in funding for their unique application of machine learning. The company has centred their business around building machine learning algorithms that automatically identify barcode-less products at supermarkets (think fresh fruit and veg). 

What is machine learning

Tiliter’s application of machine learning has a similar path to the above example, the difference being, you ar are replaced by an algorithm and Bec is replaced by customers. 

Let's have a look at how such an algorithm could be trained

Suppose a customer at Woolworth’s wants to buy a pink lady apple. As they reach the counter, you will see the barcode scanner, except this particular scanner uses a camera and a specialised machine learning algorithm in training. 

The scanner views the apple (input), spits out three possible options (outputs) as to the variety and then ranks them in order of probability. The algorithm’s first option is a granny smith, followed by a royal gala and, finally, a pink lady.

The algorithm outputs these options as images on the screen above the scanner; the customer then selects the correct option, which supplies the algorithm with the feedback it needs. This feedback allows the algorithm to refine its ability to recognise pink lady apples in the future.

Over time and through many exposures, the algorithm will develop its own mental map, categorising various produce items and their variations. After a period of time, it will become so adept at recognising the produce that it won’t require any human input.

Key takeways

Whilst machine learning can add significant value to some activities, it is by no means a panacea. When forced into applications outside of its range, it can lead to massive wastages in time, money, and energy. At the end of the day, it is best suited to specific applications such as the Tiliter example.

Thank you for reading!

Thank you for reading this article. We hope it gave you some valuable insights into the electronic product development process.

Need support?

To find out more about the electronic product development process, reach out to our experienced engineers at contact@saphi.com.au for a quick chat. 

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What to consider when choosing a sensor

What to consider when choosing a sensor

In this article, we will be walking you through what you need to consider when choosing a sensor to ensure your objectives are met.

Electronic Product Development Process

Strap yourselves in

In SAPHI’s world of monitoring, automating and integrating, sensors play a fundamental role in our day-to-day when servicing client needs. We know that there are only so many people we can physically support each day to spec, configure, deploy and integrate the right sensors, so we decided to draw up a blog post to help those of you out there that have decided to tackle the journey alone.

What you will get from this article

  1. Accuracy of sensors – how important is it?
  2. How accuracy relates to price
  3. How do sensors capture real-world data?
  4. What to consider when looking for a sensor
  5. A word of caution

Accuracy of sensors - How important is it?

Let me reach into my development bag of throw away lines and present you with a “Well that depends” to kick things off. It sounds like a cop-out, I know, but it is hard to make universal statements in the world of tech, especially when it comes to sensors. 

It is a nuanced world that requires a highly specialised skill set to assess the multitude of variables competing for attention in each project. To put it concisely, the lower the accepted margin of error, the more accurate the sensor needs to be.

Give me an example

Let’s say you are launching a rocket into space and are looking to integrate an IMU (inertial measurement unit) – a fancy term to describe those sensor units responsible for monitoring rockets’ force and angular rate – then you will want to be confident those sensors are extremely precise. A significant deviation might result in disaster!

However, if you are looking for a basic PH sensor for a tank, +/- half a PH unit will, in most cases, be acceptable.

It is all about application.

Accuracy and price

As you might have already guessed, the accuracy of a sensor tends to be proportional to the cost. The more accurate the sensor, the higher the cost. For example, take a humble turbidity sensor; prices can range from tens of dollars to tens of thousands!

The variation in price in the sensor world is extreme, so it is crucial to evaluate the value of the problem you are solving, the acceptable margin of error and commercially available options – but more on this later.

How do sensors capture real world data?

Sensors function in much the same way as the human body. Our bodies are an amalgamation of intricate sensor units that allow us to gather information on our surroundings.


For light detection, we have our eyes, sound our ears, and temperature our skin. These specialised sensors detect stimulus in the real world, convert that stimulus into an electrical impulse and send it to the brain to make sense of it and react.


Similarly, a sensor is designed to detect a change in the real world and convert it into a measurable analogue or digital signal that is sent to a processor (the brain) for processing. 


Whilst this is a crude example, it serves well to offer a high-level overview of a sensor’s function. However, should you wish to go into more technical detail, check out this article.


What to consider when looking for a sensor?

As you are aware, there is a sensor for just about everything in our world. From capturing vibration, light, movement and sound through to proximity, orientation and positioning, there is a seemingly endless list of options for each category, so how do we know which one is right for us?

I should preface the following by first acknowledging that each of these sensor categories will have its own peculiarities that can only be considered within its own category. 

For example, suppose you are looking for a sensor to detect movement. In that case, you need to first ask yourself what movement type you are measuring, linear or rotary. This important filtering question obviously only applies to this category.

With that said, the following broad considerations are critically important to ensure you select the correct sensor. Failure to do so can result in significant investments with no return. 

1. Accuracy & Price

As previously mentioned, accuracy is often proportionate to the cost, so it is vital to assess the minimum margin of error acceptable for your project.

For example, if you are looking for a PH sensor and a margin of error of +/- 0.5 of a PH point is acceptable, then there are a whole host of pretty affordable options out there for selection.

On the flip side, if you require accuracy of 0.1<, you will be looking at a more significant investment per unit. Be sure to analyse the requirements and budget to.

2. Environment

It is crucial to reflect on the environment these sensors will be operating in and for how long. Are these sensors going to be sitting in a corrosive environment or tucked away in an air-conditioned office? If they are in a corrosive environment such as a sewer or water pipe network, how long will they be in there? Hours, days, months, years? 

These questions are important to address when selecting the appropriate device as they will inform your team about the level of ruggardisation the sensor needs to function long-term.

The more corrosive the environment and the longer the length of deployment, the higher the IP rating will need to be.

3. Range

Like with accuracy, range can have a significant effect on price, in many cases, the broader the range, the more expensive it is. A temperature sensor capturing 0-100 degrees is relatively cheap, however, finding one that can capture up to 2000 degrees is going to set you back.

To filter out the irrelevant, it is critical for you to determine the range of variance you are most interested in capturing and ensure the sensor can cater for this. 

4. Data Capture Frequency

One of the most critical considerations in device specification is the frequency you need to capture data. How granular do you need the data?

Sensors will have different max frequencies that they can sample data with. The higher the number, the greater the accuracy. It is crucial to know the variability of your parameters and select a sensor that will provide the best chance to ensure those events are captured. 

What do I mean by this? Well, if an important event you wish to capture happens every minute and lasts for 5 seconds, and your device only samples every minute, you have a meagre chance of catching this event.

This is because the event may happen 10 seconds after your last sample was taken and is over before the sample is retaken 50 seconds later. Hence a higher sample frequency is necessary to ensure important events don’t slip through the frequency cracks.

5. Calibration & Maintenance

How often will your team be able to recalibrate and service in-field devices? Different sensor units and types have varying recalibration requirements. This information is usually provided by the manufacturers. 

6. Mounting & Mobility

How often will you need to move the sensor units? Will they serve their whole lives in a single location? Does the location allow for easy mounting? 

Some sensor units can be particularly large and cumbersome, leading to difficulties in deployment and extraction. Not to mention the size of the unit may, in fact, inhibit the medium you are measuring.

For instance, if you have a water flow sensor unit that takes up most of the pipe, you will constrict the water flow and potentially cause more damage than good. 

7. Availability & Reliability

When investing in vast deployments for long-term data capture, it is important to select devices with either high availability or reliability (ideally both). 

If a sensor unit breaks down, you will want to be able to replace it readily. However, suppose the lead times for the units are lengthy. In that case, you will want to ensure the reliability of the sensors is such that you can expect more time in-between failures.

A word of caution

With an insatiable global demand for data and those devices used to capture it, thousands of companies have sought to capitalise. This has resulted in an explosion of devices, all marketed as “the world’s best sensor for XYZ”. 

I fail to go a single week without being harassed by sensor companies worldwide trying to convince me that their sensor units will solve all my and my clients’ problems. 

However, the fundamental problem with this is that most of these devices talk the talk but fail to walk the walk. Our team are regularly on the phone with new clients who reach out for support after being burnt one too many times by device conglomerates. It is deeply frustrating to witness the thousands of people having their budgets chewed up for no result when they embark on their data capture journey. All due to inflated claims.

If you take nothing else from this article other than what I am about to say, I can rest a happy person: always be sceptical of sensor company claims. 


And remember – buying sensors is only half the job. Once purchased, you will need a confident team who have the expertise to program, configure and deploy the assets to ensure they reliably capture the data you value.

Thank you for reading!

Thank you for reading this article. We hope it gave you some valuable insights into the electronic product development process.

Need support?

To find out more about the electronic product development process, reach out to our experienced engineers at contact@saphi.com.au for a quick chat. 

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Electronic Product Development Process

Electronic Product Development Process

In this article, we will be taking a deep dive into the electronic product development process, the steps involved in converting your innovative ideas into reality and what you can expect at each stage of the journey! 

AI company

Electronic Product Development Process

To be relevant in the rapidly evolving market we live in today, companies have to work hard to remain relevant through the development of new, innovative products through a well-executed development process. Out of the millions of lightning bolt ideas people have each day in the shower, few ever see the light of day as a commercially viable product. 

Now, we can develop a list of a thousand and one reasons as to why this is the case, such as lack of capital, time, resources, expertise etc. But the most significant barrier to entry is the age-old problem of “I simply don’t know what I don’t know”.

Without a fundamental understanding of each step in the electronic product development process and the efforts required for each, ideas will forever remain just that. Ideas. 

In this article, we will be guiding you through the exciting world of electronic product design and development – what each step in the process is, what to expect and most importantly, how to start.

What you will get from this article

  1. Where to start
  2. Proof of concept
  3. Iteration
  4. PCB design & development
  5. Industrial design
  6. Manufacture

Where to start

With the assumption that you have thoroughly researched your idea, the competitive landscape and price points for your solution, the first step in your electronic product design and development process is concept testing and validation.

Concept Testing & Validation

This is a simple yet crucially important component of the overall process that cannot be overstated. This initial step will establish the basic foundations your product will be built upon moving forward. 

In this phase of development, you will be identifying critical consumers within your target market that are not only experiencing the problem you are setting out to solve but are actively looking for solutions. Once identified, you will need to quiz them on what an ideal solution to this problem looks like – what is essential, what would be the minimum number of features they would need to satisfy their needs? 

Be careful not to ask leading questions that direct consumers to your solution – this step should be as free from bias as possible. You are looking for honest, open feedback that you can mould your initial concept around.

What is the goal here?

This phase aims to have an open-ended discussion with your target market to identify discrepancies between what you think is important and what is actually important to the end-user.

What is the outcome from this phase?

By the end of this phase, you should have a concise list of the most valuable core features your target market needs to solve their problem. It is essential when developing this list that you cluster and separate the “would be nice to haves” from the “must-haves”. This list should only contain the critical features your target market cannot live without. This is your starting point.

Proof of concept

With your list of must-haves defined, you are now ready to convert this list into a tangible proof of concept to demo to your target market. 

What is the goal here?

In this phase, you are not looking for a polished product, merely a functional prototype using off-the-shelf hardware to validate the results of your concept testing. For example, the image below is an initial proof-of-concept our team developed for an agricultural client to validate the feedback they received from consumers. 

Rather than investing in expensive, custom hardware development upfront, our client leveraged our skills to integrate off-the-shelf technology to rapidly develop a tangible prototype that they used to validate their product idea for a fraction of the cost. Our client was able to leverage this proof of concept to secure investment and advance through the process to commercialisation.

Electronic Product Development Process

The over-arching goal of this phase of the electronic product development process is to see if reality matches the initial hype from the consumer.

What do I mean by this?

Remember the adage “actions speak louder than words”? Well, when it comes to electronic product design & development, this has never been truer. Though your target market may shout to the hills that they would snap up your product in a heartbeat, when push comes to shove and the opportunity to secure a unit arrives, their actions often tell a different story. 

This rarely comes from a place of malicious intent, rather from the perspective that perhaps the solution doesn’t exactly solve the problem the way they imagined. This is why it is crucial to get a functional prototype up and into the hands of consumers to analyse their actions before investing further resources into the project.

What are the outcomes from this phase?

At a high level, you are looking to convert the list of must-haves into a working prototype that you can use for further testing, which segways nicely into the next phase.


With a proof of concept in hand and an understanding that negative feedback is the best kind of feedback, you are ready to iterate. In this phase, you will be beta testing with users to obtain as much feedback as possible regarding the current state of the product. 

What is the goal here?

You will be looking for consistencies in the feedback provided by your early adopters. The goal is to develop a tangible set of features and/or tweaks to existing features that align the product to the ideal solution your consumers are dreaming of. 

What is the outcome from this phase?

The outcome from this phase is to circulate these features and tweaks back to your development team to use to refine the prototype. 

PCB Design & Development

Once you have completed beta testing and have a validated proof of concept in hand, you are ready to dive into the exciting and complex world of custom PCB design & development. In this phase of the electronic product development process, you will be preparing your concept for mass manufacture. This step reduces the form factor of your prototype, significantly reduces the cost per unit and improves performance efficiency.

What is the goal here?

The goal is to convert the stack of off-the-shelf electronics used for your prototype into a singular, streamlined board that prepares your product for mass production.

What is the outcome from this phase?

The outcome from this phase of the electronic product design and development process is to produce a custom printed circuit board design that manufacturers can use to develop your electronics in mass quantities.

Industrial Design

Now you are on the home straight. In this phase, you will see the fruits of your labour come together in a sleek, professional design that makes your product look like the finest quality piece of equipment out there on the market. When it comes to selling products, the look and feel signals to prospective consumers what the quality of the product is like. The better the product looks, the higher the perceived quality – the higher the perceived quality, the more you can charge.

What is the goal here?

The goal here is to define your product’s end look and feel, converting your vision into reality, ready for final testing on your target market.

What is the outcome from this phase?

The outcomes from this phase are to produce high-fidelity prototypes of your product and to prepare the design for mass manufacture.


You made it! At this point in the process, everything looks amazing, performs as designed and is ready to hit the market running (provided you have secured all of your patents!). Here, you will have secured a partnership with a reliable manufacturing company specialising in electronic manufacture and settled on a minimum order quantity to produce your first batch.

What is the goal here?

The goal here is to solidify your relationship with your manufacturer and define the minimum order quantity for your first order.

What is the outcome from this phase?

The first generation of your polished, fully functioning products!

Thank you for reading!

Thank you for reading this article. We hope it gave you some valuable insights into the electronic product development process.

Need support?

To find out more about the electronic product development process, reach out to our experienced engineers at contact@saphi.com.au for a quick chat. 

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How To Power IoT Devices

How To Power IoT Devices

In this article, we will be diving into all things to do with power to answer the fundamental question – How to power IoT devices? We will be discussing where to start, key power management considerations, the options available to you based on the power consumption of IoT devices and to wrap things up we will share case studies for each option.

How to power IoT devices

How To Power IoT Devices

In a world where digital technology reigns supreme, IoT has rapidly become an integral character in our lives and unleashed an entirely new way of solving problems and generating value. IoT’s impact on industry has been so transformational that it has given rise to what has now been coined the fourth industrial revolution (industry 4.0), aka the industrial internet of things (IIoT).

These devices, when properly configured, derive meaningful information that has fundamentally altered how our businesses operate. Companies such as Google, Amazon and even Disney Land have integrated IoT into their businesses to unlock latent value and improve their processes.

However, despite IoT providing almost unlimited opportunity to solve some of our worlds most significant problems, one of the most limiting factors in its usage is keeping its devices powered in the field. 

So what are the options available to me and my team to keep my devices running and producing value? Read on to find out.

What you will get from this article

  1. Where to start
  2. How to measure power consumption of IoT devices
  3. The four most common power supply options for your IoT devices
  4. Defining the right supply for you 
  5. Case studies 

Where to start

The fundamental starting point for utilising IoT in the field is determining the power consumption of IoT devices you wish to deploy. Whilst IoT can do everything from logging water quality in a dam once per day to providing live stream video footage for artificial intelligence models, the methods of power supply required to run these operations are vastly different.

For instance, continuing from the example above, a basic IoT system using an Arduino to log water quality once per day in a remote location can comfortably run on a small battery topped up by a small solar panel for multiple years. This is because the device is only required for a split second each day to log a tiny data packet and can be programmed to ‘sleep’ for the remaining 23hrs 59min of the day until it is needed again. 

However, the same cannot be said for video imaging. Video is far more energy-intensive and requires a more powerful controller such as a raspberry pi to capture, process and communicate the data to a database. The resulting data packet is far larger than that of a water quality reading and thus requires a more powerful and consistent power supply. Therefore, the video application would not be a good candidate for remote locations with no direct 240v power sources.

Is it impossible? No. Nothing is impossible in this space, and there are definitely workarounds, but this is what we must consider when balancing functionality and power.

How to measure power consumption of IoT devices

When it comes to deciding on the right power supply for your project, the first step is to analyse the power consumption of the devices you wish to deploy.

The most efficient and accurate way to assess this is to utilise power analyser tools such as the Otii which enable you to get accurate readings on power consumption. (I promise we do not have any affiliations with Otii, we just think it is a great tool).

Once you hook up your device to the power analyser of your choice and connect it to your desktop, you will get a graph reading like the one below. If you are unsure how to hook up your device to your power analyser, the maker of your model should have documentation on their website on how to do so.

Power consumption of IoT devices

With the power analyser we can determine the current (bottom) and the voltage (top), which we multiply together to get the power (watts) consumption. As you can see in the above image we have periodic spikes of power which indicate when the device is awake and transmitting information. A closer examination of these spikes can be seen below.


Power consumption of iot devices


By analysing the power consumption at rest and during transmission, we can accurately predict how long these devices can operate with different power supplies. The real balancing act here is deciding on the length of time the device needs to be powered in the field and how often it needs to be transmitting data.

Why is this important?

As the number of transmissions increases, so to does the average power consumption. To maximise outcomes, our goal is to determine the minimum frequency of operation that generates the desired value. By reducing the frequency of transmissions where possible, we can dramatically increase the operational life expectancy of devices.

For example; a client might want to monitor the water and sewer levels of their networks and they have a series of devices that are logging data every second. However, they determine that a reading once a minute would surfice, so by writing a few lines of embedded code to alter the transmission frequency, we can extend the life of the devices by a factor of 60! 

By determining from the outset where the lines cross between operational frequency and life of assets you will be operating from a position of maximium efficiency, saving time, money and effort.

Most common IoT power supplies

With all that said, let’s dive into the three most common methods of power supply for IoT devices and determine which option is right for you and your project.

1. Mains supply

In simple terms, mains power refers to the electrical supply from power stations to our homes and businesses which we access through our powerpoints. Every time you plug in your laptop, phone charger or microwave, you are leveraging mains electricity. 

When to use mains power for your IoT devices?

Generally speaking, whenever we have access to mains power, we would utilise it as it offers the most reliable, consistent power supply to our devices. 

Mains power is often required when we are using IoT systems and devices that have significant power consumption requirements that exceed the limits of battery power. The following applications would be considered high power:

  • Camera/video imaging
  • Real-time data capture with multiple parameters
  • Digital displays 
  • Systems with multiple devices running at the same time (e.g. turbidity sensors, PH sensors, Air quality etc.)

Pros of mains

  • Most reliable source of power
  • The largest supply of power
  • No additional investment in batteries required

Cons of mains

  • Limited access points
  • Usually unavailable in remote environments
  • Often has significant regulatory barriers to tap into the supply for most commercial properties

Case study example

In 2020 our team at SAPHI developed a bespoke digital signage display controlled via a custom mobile app for a large CommBank facility in Sydney.

Because the system was required to power and control large LED panels 24 hours a day, the power requirements were far too high to run off battery. This meant the solution required access to a mains power supply to operate.

2. Vehicle battery

If your device is designed to be used in or around vehicles, tapping into the power supply of the vehicle is often a viable option.

When to use vehicle power for your IoT devices?

Whenever your device is mobile and is frequenctly in or around vehciles, tapping into the vehicle’s alternator will give you a steady supply of reliable power. The following applications could be considered good use cases for vehcile power:

  • Extracting data from vehicles
  • Vehicle monitoring (temperature, pressure, location)
  • Digital displays 

Pros of vehicle of battery

  • Large and reliable source of power
  • Enables use of mobile IoT devices
  • No additional investment in batteries required

Cons of mains

  • Can deplete battery of vehicle if devices are too power hungry
  • Device will only run when vehicle is on
  • Device size is limited depending on size of vehicle

Case study example

BHP was having difficulty managing and tracking the health of its assets. They needed a way to predict failures before they occurred in order to extend the life of their assets. 

SAPHI designed and developed an industrial CAN bus vehicle sniffer system that enabled BHP to extract the data from its mining equipment and have it integrated into its predictive analytics system. The system had no access to mains power and was too power hungry to run on its battery alone so we designed the system to tap into the alternator of the vehicles to obtain the power it needed.

3. Solar + Battery

If mains supply is not an option, then a common alternative (provided the device is in direct contact with sunlight) is the use of a battery with attached solar system .

The battery supplies the necessary power and is topped up by the additional renewable energy from the solar panel to extend its operational life.

When to use battery + solar power for your IoT devices?

Battery and solar is a common power supply method for devices in remote areas that need to remain operational for longer periods of time than what a battery alone could support. 

The following applications would be considered good applications for battery + solar:

  • Remote monitoring applications e.g. environmental monitoring (waterways, pipelines etc.)
  • Remote actuation of systems based on monitor readings e.g. dosing water based on PH levels
  • Applications that require systems to be left in the field for long periods of time 

Pros of battery + solar

  • Enables the remote deployment of many IoT devices and systems for longer periods of time than battery alone
  • Provides a consistent source of power to devices when mains power is not available
  • Enables the use of smaller, more compact batteries as they are able to be recharged regularly
  • Depending on the power consumption of IoT devices, how often they are switched on and the size of the battery, devices can last for weeks, months or even years before needing to be changed

Cons of battery + solar

  • Requires investment in battery and solar panels which can be costly if the IoT system is large and complex
  • Must have access to direct sunlight
  • Cannot handle high-powered operations for long periods of time

Case study example

SAPHI have developed a series of battery + solar powered systems over the past six months to address the problems our clients were having around getting reliable readings on the quality and levels of their water. Our team recently developed three major systems for PH and turbidity detection as well as water level monitoring. 

Each system has been deployed in remote, arid locations around Australia with direct access to sunlight and have been reliably logging the data they have been programmed to since their inception, providing on-going value to users. 

4. Battery

If you have no mains supply and solar is not an option, then the 3rd best option is battery power for operating your IoT devices.

When to use battery power for your IoT devices?

Battery is a common option for power supply when we do not have access to mains power or solar supply. Battery is a great option for very low powered devices that are deployed in remote locations.

The following applications would be considered suitable applications for battery:

  • Remote monitoring applications that do not require real-time data  
  • Applications that only require the device to operate for small periods of the day

Pros of battery

  • Enables the remote deployment of some IoT devices and systems
  • Provides a reliable source of power to devices 
  • Depending on the power consumption of IoT devices, how often they are switched on and the size of the battery, devices can last for weeks, months or even years before needing to be changed.

Cons of battery

  • Depending on the power draw of your devices, you may require large battery systems which can prove costly.
  • They limit the rate and amount of data you can collect
  • They cannot handle high-powered operations for long periods 

Case study example

Earlier this year, SAPHI developed a wearable COVID tracing system for a UK investor-backed startup. The system was designed using specialist technology to alert and trace in time, the user’s interactions with people who later tested positive for COVID-19.

Because the system was able to be regularly charged, we designed the solution to accommodate a small battery that would comfortably run through the day before needing to be topped up.

So which option is right for you?

Unless you have an engineering or electrical background, there might be a bit of a learning curve when it comes to selecting the right option that will ensure the longevity of your IoT systems, especially the edge cases where there is no clear answer. However, as a rough rule of thumb with a multitude of exceptions:

  1. If you have access to mains power and your devices can handle a 240v connection, go with that
  2. If your device is designed for vehciles, than tap into the alternator for a reliable power source.
  3. If you need to capture data in areas without access to mains supply but has direct sunlight, go for the battery with solar option
  4. Finally, if options one and two are not available, go for the solo battery
Note: it is critical to assess the power consumption of your devices when you are deploying your solutions. In many cases, the power requirements for solutions may be too high to make battery and/or solar a viable option without some customisation. By utilising power analyser tools and having a software developer by your side, you can find the perfect balance between longevity of devices and generating maximum value!

Thank you for reading!

Thank you for reading this article. We hope it gave you some valueable insights into power management and what option might be best for you.

Need support?

To find out more about what would work best for your individual circumstance, I encourage you to reach out to our team here at contact@saphi.com.au for a quick chat. 

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How to send sensor data to the cloud

How to send sensor data to the cloud

In this article, we will be looking into 5 smart ways that answer the question we are all here for – how to send sensor data to the cloud?

How to send sensor data to cloud

Choosing is hard

With so much choice in IoT infrastructure on the market, nailing down the right options can be overwhelming. Once you finally do, however, the inevitable question arises “How am I going to get the data to the cloud?”

In this article, we will be showcasing five smart options of how to send sensor data to the cloud, and we will be breaking each option down based on their:

  • Bandwidth
  • Cost
  • Coverage/range – Please note range heavily varies on several factors such as humidity, obstacles, antenna design/positioning etc. the ranges we give are general in nature.
  • If they offer real-time insights

The 6 Methods

  1. Starlink
  2. Wi-Fi
  3. 4/5G
  4. CAT M1
  5. NB-IoT
  6. LoRA

1. Starlink

Starlink provides high-speed, broadband internet across almost the entire globe. This game-changer is enabling the mass deployment of high bandwidth IoT devices in the most rural and remote areas of Australia.

Bandwidth: High – Starlink service agreement guarantees speeds of 50 – 150 Mb/s, and in our own tests, we recorded speeds of up to 300 Mb/s. This makes it a great option for transmitting large and/or frequent amounts of data in image, video or text format.

Cost: Upfront cost of $700 for the hardware and ongoing costs of $140 per month.

Coverage & range: Covers significant portions of the globe, with coverage increasing every month. See the current coverage map here

Real-time data insights: Yes

When to use: When you have the requirement for high bandwidth in a rural or remote location.

Example: Rural and remote worksites leveraging multiple IoT devices to capture real-time data insights on asset performance and weather conditions.

2. Wi-Fi

When it comes to wireless IoT protocols, Wi-Fi is the most popular due to its widespread presence. Generally speaking, if Wi-Fi is available in the area devices are deployed, Wi-Fi will be used.

Bandwidth: High depending on plans – Wi-Fi varies from 10s of megabits per second to 1000s – enabling you to send bulky messages such as images and video with ease.

Cost: If you already have Wi-Fi in the area, it requires no additional cost (provided you have an unlimited plan).

Coverage & range: Low up to 50m. However, you can increase this range with Wi-Fi repeaters. The amount you can increase the range, however, is dependent upon the level of interference in the location. Coverage is not applicable.

Real-time data insights: Yes

When to use: Whenever your devices are within range of a Wi-Fi router.

Example: Just about anything involving capturing and transmitting data. It could be used for things such as live security camera monitoring systems, image processing, weather monitoring, machine performance monitoring etc.

3. 4/5G

The mobile 4G and 5G networks are regularly used in the IoT space and are generally the choice for many people looking to transmit bulky messages to the cloud but have no Wi-Fi access.

Bandwidth: High depending on plans –  Suitable for sending bulky messages such as images and video.

Cost: High – you need to purchase sim cards and subscription plans for your devices to have your messages sent. The bill you receive at the end of the month will depend on the size and frequency of messages being sent.

Coverage & range: High, up to 70km. With added infrastructure, this can reach 150km in some locations. Whilst the mobile coverage is good in and around most towns and cities, you can see it drops off heavily in rural and remote parts of Australia.

Real-time data insights: Yes

When to use: When you need a lot of bandwidth but have no access to Wi-Fi.

Example: Our team developed a live stream security monitoring system for several clients who wanted to monitor and receive alerts when would-be thieves and vandals approached their sheds where they stored their equipment and machinery.

Getting data to the cloud

4. CAT M1

CAT M1 is a low-power wide-area cellular technology, similar to 4G and 5G, but has been built specifically for IoT projects requiring the transfer of low to medium amounts of data infrequently over a wide area for long periods.

Bandwidth: Low 1 Mb/s.

Cost: Lower than 4G and Wi-Fi but more than LoRa and NB-IoT.

Coverage & range: Very high, up to 100km, and it has the second broadest coverage of the mobile networks (see below).

Real-time data insights: Yes.

When to use: When you need higher bandwidth when monitoring in remote locations.

Example: Our team developed a series of wind turbine and weather monitoring systems in remote locations around Australia that capture real-time insights on 50 different parameters, 25 times per second.

CAT M1 Network

5. NB-IoT

Like Cat M1, narrowband IoT (NB-IoT) is a low-power-wide-area cellular technology and is a popular wireless communication standard in the IoT space. NB-IoT allows users to connect devices collecting small amounts of data at low bandwidth, using very little power.

Bandwidth: Low – 200Kbps.

Cost: Lower than 4G but higher than LoRA.

Coverage & range: Very high, up to 120km and has the broadest coverage of the mobile networks (see below).

Real-time data insights: Yes.

When to use: Monitoring in remote areas with low power requirements.

Example: A real-time data system to track temperature-sensitive goods. We have seen this excellently applied to monitoring the temperature of kegs in transit to ensure they remain refreshingly crisp. Another recent example is its use in tracking the temperatures of vaccines in transit!

How to send sensor data to cloud

6. LoRA

A popular network among councils is the LoRA network – a low-power, wireless
network communication protocol. LoRA requires line of sight to what are known
as “LoRA gateways” to send messages to the cloud.

Bandwidth: Very low – max 11Kbps.

Cost: Around $600 for your own gateway. However, if
you are within range of other established gateways, you can tap into those.

Coverage & range: Each sensor network can provide
10-40km of range on range.

Real-time data insights: No.

When to use: When you have many sensors in a relatively small area – Agriculture sensors, smart city projects (bin sensors, pedestrian counting etc.).

Example: A great use of LoRA is exemplified by several smart cities we have supported; One example is the implementation of sensors to monitor bin levels that notify maintenance workers when levels are full or nearing capacity. 

Another is the use of LoRA to monitor the amount of vehicle and foot traffic in areas around the city to better inform cities where they need to invest in infrastructure. And finally, its use to track the number of free and occupied parking spots in the CBD.

Thank you for reading!

Thank you for reading our article on How to send sensor data to the cloud! We hope it gave you a better idea of which method of communication will work best for you!

Have more questions?

To find out more about what would work best for your individual circumstance, I encourage you to reach out to our team here info@saphi.engineering for a quick chat. 

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Smart city ideas and suggestions

Smart city ideas and suggestions

In this article we will take a quick dive into the smart city ideas and suggestions you should know

Smart city ideas and suggestions

Smart City Ideas & Suggestions

The Smart City movement is currently one of the most important and innovative topics in technology. Smart Cities are changing the way we live, work, and play. In this blog post, we will discuss key points to consider when approaching a new smart city project, what questions to ask and ideas on projects you can begin implementing into your City today to make it more successful.

What you will get from this article

  1. Where to start?
  2. Defining a good problem
  3. Defining a good solution
  4. How to test to maximise outcomes
  5. Maintenance considerations
  6. List of Smart City project ideas
  7. What to pick?

1. Where to start

With a good problem… 

It may sound obvious, but far too often do we see smart cities investing in off-the-shelf solutions without first defining a valuable problem that needs solving. It is easy to get carried away by the claims of many IoT devices on the market today – each promising to solve all our problems with the flick of a switch. 

However, it is important not to fall into the trap of finding an awesome new gadget and then working backwards to find a problem it can solve.

With all the smart city ideas and suggestions outlined in this article, it is critical to have a clear view of the problem you are looking to solve before making a purchase.

2. Defining a good problem

The first step in defining a good problem is to first narrow down the field by answering the following questions:

  • What are the top of mind pain points of your department?
  • Which of these problems is costing you the most time/money/ headaches?
  • Which of these problems could be solved or reduced through automation or quality data?
  • What will the outcomes be once this problem is solved?

3. Defining a solution

Once a problem has been identified, the next logical step is to determine the viable solutions currently available on the market that will produce the outcomes you want. 

A word of warning; companies’ whose business model is focused on selling sensor units will claim some pretty wonderful things, however, these claims should be taken with a heavy grain of salt. 

Smart city sensors are not magical devices that can solve all of the problems in a certain area, rather they should be seen as tools used to collect data which will then need further processing and interpretation by humans before actionable insights are gained. 

When assessing the solutions on the market; be sure to do your due diligence:

  • What are the claims of the device?
  • What are forums external to the company saying about it?
  • What are the on-going costs?
  • Does the company lock you in and make it hard to switch approaches down the track?

4. How to test to maximise outcomes

So you have defined a good problem, found a viable solution and now looking purchase a batch of systems. Before you send off that purchase order stop, think and test. Smart city projects are expensive, so it is important you are investing in the right solutions that will provide value for years to come. 

The first test would be to look to those who have already purchased the product and implemented it:

  • What were their thoughts?
  • What did they learn from the experience?
  • What sort of results were generated?  

Hot tip: Look up independent opinions external to the company website to get an objective opinion. 

Once you have completed your concept test, it is time to move on to the physical one – testing the claims of the device out for yourself. Order 1-2 samples for yourself and construct a test environment to put the devices through their paces. 

Our team at SAPHI recently completed this for a council in the Hunter who wanted to determine if their cyclist counter lived up to the claims on the website before placing a large order. Fortunately, before the purchase order was signed, our team were able to put the device through a series of controlled tests that uncovered the device was in fact, a lemon. 

This is a highly common story in Smart City projects – the devices look great on paper but when they get out into the field the results tell a different story.

5. Maintenance considerations

Once you have the device configured, connected to a database and deployed – the real work begins. IoT devices are far from set and forget solutions. Much like that veggie garden you have set up and killed several times over the years, the systems you have deployed in the city require constant attention to keep them alive and kicking. 

For this reason, it is vital to have a management team and strategy in place, before you purchase, to ensure your devices stay at their peak and continue to bring value to your city long-term.

6. Smart City Ideas & Suggestions

It’s difficult to say what will work and what won’t. As you know, each city is unique and has different priorities. However, with that said, here are some smart city ideas ranging from quick wins to large scale projects that have the potential for long-term success:


  • Soil monitoring: Smart soil monitoring is a smart city idea that are relatively inexpensive and simple to install. Smart soil monitors are useful pieces of technology for keeping track of the status and health of your city’s gardens.


  • Pedestrian counting: a small scale pilot project for pedestrian counting can be a quick, cheap and easy way to gather data from citizens. This information is invaluable for understanding commuting habits which can inform where the city should focus on developing, upgrading or diverting.


  • Smart parking: Smart parking systems can be installed in a matter of weeks and will enable citizens to access available spaces with ease. Additionally, data on parking habits around the city can indicate to the council where they should focus their efforts on creating new parking spaces.


  • City pothole detection: A simple accelerometer attached to a garbage truck can be enough to give decision-makers the data they need to determine road sections of concern that need attending to. Furthermore, for more accurate results, a basic AI camera system can provide not just alerts, but detailed images of the size and scope of the holes detected.


  • Indoor air quality: Smar air quality systems can be used to detect and assess the air quality within your buildings. With these systems, you will have an insight into the temperature, airflow, carbon dioxide levels and humidity of workspaces so you can make informed decisions to keep your spaces happy and healthy for all.


  • Pollution tracking: In areas where there is a significant amount of traffic, the pollution levels can be troubling. Smart city projects involving air quality sensors that work with to produce detailed and meaningful data on how much pollutants are in the air.


  • Smart alert system: Custom-developed smart alert systems are a smart way to trigger workflows for the relevant council team members when predefined parameters are met. For example; when soil moisture is low or potholes are discovered etc. notifications are triggered by the system and workflow alerts are sent to the maintenance teams to amend the problem. A central, integrated alert system is an invaluable method for reducing the manual labour ordinarily associated with manual checks and workflow requests.


  • Smart street lighting: Smart street lighting uses the latest technology to reduce the energy usage of traditional street lights. Smart lights can automatically adjust their brightness based on periods of inactivity; they can also transmit maintenance information for quicker response times. 

7. The burden of choice. What to pick?

With a saturated market of IoT solutions targeted towards smart cities, it can be a nightmare to nail down the right option for you. 

One thing I am very passionate about having grown up in a small council district is ensuring budgets are not wasted on hollow promises. For this reason, if you need some advice on what would be the right smart city project/device choice for you, feel free to reach out to our team for a chat. 

We are happy to volunteer an hour or so of our time to point you in the right direction, offer some advice on what to look out for and give you some tips on implementation.

Thank you for reading!

Thank you for reading this guide! We hope it gave you a better idea of
which method of communication will work best for you! 


Have more questions?

To find out more about what would work best for your individual circumstance, I encourage you to reach out to our team here info@saphi.engineering for a quick chat. 

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