AI-IVMS

AI-IVMS

SAPHI developed, integrated, and now manage a cutting-edge mining IVMS, powered by advanced AI models. Our system ensures operator safety and optimizes routes for maximum efficiency.

AI imaging and recognition

What Was The Problem?

In the demanding environment of mining operations, safety and efficiency are paramount. One of our clients, a tier 1 mining company, faced significant challenges in ensuring the safety of their operators and optimizing transport routes within their mines. 

 

Their existing vehicle monitoring systems were outdated and lacked the real-time capabilities necessary to respond swiftly to hazardous conditions and operational inefficiencies. The client needed a solution that could provide real-time data in some of the most remote areas, enhance safety protocols, and optimize transportation routes to reduce fuel costs and improve productivity.

What Was The Solution?

To address these challenges, SAPHI implemented the Shellshock AI-IVMS (In-Vehicle Monitoring System), a sophisticated solution backed by the latest AI models. The Shellshock AI-IVMS was designed to provide real-time monitoring, ensuring both the safety of operators and the efficiency of mining operations.

 

Key features of the Shellshock AI-IVMS included:

  • Real-Time Monitoring: Continuous monitoring of vehicles and operators, providing instant alerts for hazardous conditions and equipment malfunctions.
  • Route Optimization: AI-driven route planning to optimize transport routes within the mine, reducing fuel costs and enhancing operational efficiency.
  • Evergreen Technology: The system is designed to be evergreen, with the capability to be remotely extended and updated. This ensures that the solution evolves with the client’s needs and the latest technological advancements.
  • Seamless Integration: Integration with existing mining management systems for comprehensive data analysis and reporting.

What Were The Results?

Our successful deployment of an AI-IVMS for our client, a leader in mining, showcases our ability to deliver tailored AI-driven solutions. This solution improved operational safety and compliance monitoring. Key outcomes included: 

 

The implementation of the Shellshock AI-IVMS solution led to significant improvements in the client’s mining operations. Key outcomes included:

  • Enhanced Safety: Real-time monitoring and instant alerts drastically improved the safety of operators, reducing incidents and ensuring compliance with safety protocols.
  • Increased Efficiency: Optimized transport routes reduced fuel costs and minimized downtime, leading to a significant boost in overall productivity.
  • Operational Insights: The integration of the Shellshock AI-IVMS with existing systems provided the client with comprehensive operational insights, enabling data-driven decision-making and continuous improvement.
  • Evergreen Capability: The ability to remotely update and extend the system ensured that the client could continuously benefit from the latest advancements and customizations tailored to their evolving needs.
  • Global Implementation: The success of the system in initial deployments led to its trial in multiple locations, including Australia, Malaysia, and India, demonstrating its scalability and effectiveness across different mining environments.

Learn More About Shellshock AI-IVMS

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Workshop utilisation

Workshop utilisation

SAPHI streamlined the operations of a vehicle manufacturer, optimizing its utilization rates and significantly improving throughput. By leveraging smart process enhancements and data-driven insights, we enhanced workshop efficiency.

AI company

What Was The Problem?

Workshop operations, pivotal to manufacturing efficiency, were plagued by bottlenecks and inconsistencies. The existing system lacked the capability to efficiently allocate resources, resulting in substantial downtime and underutilization. With production targets not being met and costs escalating, there was a pressing need for an innovative solution to revamp the utilization rates and bring the workshop back to optimal productivity.

What Was The Solution?

SAPHI designed a state-of-the-art machine vision solution tailored to monitor workshop operations in real-time. This system delves into the granular details, capturing utilization breakdowns—from computer time, time spent searching for parts, to actual hands-on tool operations. The system employs advanced algorithms that analyze this captured data, pinpointing inefficiencies and areas of concern. All this information is discreetly gathered without disrupting the daily operations, offering a clear lens into the heart of the workshop’s productivity challenges.

What Were The Outcomes?

Implementing our AI imaging solution revolutionizes workshop operations by addressing key challenges and enhancing overall efficiency. By leveraging advanced technology, we provide comprehensive oversight and actionable insights that empower the workshop floor and drive significant improvements in productivity and cost management.

 

  • Dramatic Cost Savings: Significant reduction in operational costs through optimized resource allocation and minimized downtime.
  • Reduced Maintenance Needs: Lower maintenance requirements due to proactive monitoring and efficient use of workshop resources.
  • Enhanced Workshop Oversight: Clear visual analytics provide comprehensive oversight, ensuring better management and coordination.
  • Top-Tier Data Quality: High-quality data is crucial for generating actionable insights and making informed decisions.
  • Substantial Cutbacks in Operational Inefficiencies: Streamlined operations lead to a significant decrease in inefficiencies and bottlenecks.
  • Immediate Feedback on Workshop Activities: Real-time monitoring and feedback improve responsiveness and operational agility.
  • Empowered Workshop Floor: Data-driven decision-making tools empower the workshop floor, enhancing productivity and effectiveness.

What Support Did SAPHI Offer After Completion?

SAPHI provides customised packages to support the full system development life cycle and implementation of upgrades to support the evolving needs of our clients and their customers.

 

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City Optimisation Using AI

City Optimisation Using AI

SAPHI developed a fully integrated AI platform to analyze pedestrian mobility and utilization in local government areas. This cutting-edge solution provides AI-driven insights for infrastructure management and urban planning, enabling more informed decision-making and optimized resource allocation.

What Did Glenelg Shire Say?

"Integrating Shellshock AI into our framework has greatly enhanced our asset management capabilities. With Shellshock AI, we've seen marked improvements in visualising pedestrian flows and our Marine traffic patterns, which has been instrumental in optimising the Local Ports asset management strategies."
Glenelg Shire Council
Team

What Was The Problem?

Glenelg Shire Council LGA needed to monitor and assess boat ramp patronage and pedestrian flow to improve urban planning, infrastructure management and optimise space usage. The geographical areas they needed to cover and budget restrictions meant traditional road ropes and IoT people counters were not going to achieve the outcomes.

What Was The Solution?

Our team developed Shellshock AI. Shellshock AI leverages advanced AI models to analyze pedestrian mobility and utilization in local government areas for a fraction of the cost and effort associated with traditional IoT solutions. 

 

 

Key features of the solution included:

  • AI-Driven Analytics: Utilized sophisticated AI models to analyze data on community engagement and recycling program effectiveness.
  • Durable Hardware: Devices built to withstand extreme weather and environmental conditions, ensuring reliability and longevity.
  • Off-Grid Power Solutions: Integrated solar power systems and battery storage to maintain uninterrupted operation without reliance on mains power.
  • Real-Time Monitoring: Enabled real-time data capture and analysis, providing immediate insights and actionable information to optimize staff schedules and resource allocation.
  • Multi-Parameter Capture: The system can monitor and analyze multiple parameters simultaneously, offering a comprehensive view of community engagement and operational performance.
  • Remote Updates: Capable of changing what parameters it captures through remote software updates, allowing for flexibility and adaptability to evolving needs.

 

What Was The Outcome?

The urban mobility solution provided the Glenelg Shire Council with valuable insights for urban planning. Key outcomes included:

 

  • Real-Time Data: Enhanced decision-making with immediate access to utilisation data.
  • Operational Insights: Improved understanding of usage patterns, aiding in the optimisation of public space and infrastructure planning.
  • Cost Efficiency: Leveraging existing infrastructure minimised costs and facilitated rapid deployment.
  • Improved Maintenance Scheduling: The data gathered allowed for more accurate and efficient maintenance scheduling, reducing downtime and improving safety.
  • Utilisation Assessments: The insights gained from the monitoring system enabled better assessments of jetty utilisation, supporting resource allocation and planning.
  • Improved Tourism Planning: By understanding the patterns of jetty usage, the LGA could enhance tourism planning, ensuring that the jetties remain a major tourist and economic asset.

Want to learn more about Shellshock AI?

See Shellshock AI for yourself by clicking the link below.

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Waste Facility Patronage Counting

Waste Facility Patronage Counting

SAPHI developed Shellshock AI. This cutting-edge solution provides AI-driven insights for infrastructure management and urban planning, enabling more informed decision-making and optimized resource allocation.

What Did LMCC Say?

"Working with SAPHI has provided us with robust, real-time data processing at the source, meeting our privacy requirements and significantly improving our asset optimization and service management capabilities."
Daniel Hartin
Asset Optimisation

What Was The Problem?

Lake Macquarie City Council (LMCC) faced the challenge of evaluating the effectiveness of their new community recycling program while also needing to optimize staff schedules. Accurate insights on patronage were crucial to understand how the community was engaging with the program.

What Was The Solution?

To address these challenges, SAPHI implemented Shellshock AI, An advanced AI-driven monitoring system designed to capture accurate insights on patronage.

 

Key features of the solution included:

  • AI-Driven Analytics: Utilized sophisticated AI models to analyze data on community engagement and recycling program effectiveness.
  • Durable Hardware: Devices built to withstand extreme weather and environmental conditions, ensuring reliability and longevity.
  • Off-Grid Power Solutions: Integrated solar power systems and battery storage to maintain uninterrupted operation without reliance on mains power.
  • Real-Time Monitoring: Enabled real-time data capture and analysis, providing immediate insights and actionable information to optimize staff schedules and resource allocation.
  • Multi-Parameter Capture: The system can monitor and analyze multiple parameters simultaneously, offering a comprehensive view of community engagement and operational performance.
  • Remote Updates: Capable of changing what parameters it captures through remote software updates, allowing for flexibility and adaptability to evolving needs.

What Was The Outcome?

The community waste facility patronage counting system provided valuable insights, justifying the investment in the community recycling program and enabling accurate staff scheduling and planning. Key outcomes included:

 

  • Real-Time Data: Enhanced decision-making with instant access to accurate patronage data.
  • Operational Insights: Improved understanding of infrastructure conditions and service optimisation. This improved patronage forecasting and planning, enabled justification of council investment in the community recycling program, optimised maintenance schedules and facility planning.
  • Reliability: Consistent performance in challenging environments.
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Would you like to learn more about Shellshock AI?

Find out how Shellshock AI is supporting local governments around Australia.

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Roadway Traffic Assessment

Roadway Traffic Assessment

SAPHI deployed Shellshock AI to capture and analyse roadway utilisation data and leverage insights to inform infrastructure planning, traffic management and maintenance.

What Did Glenelg Shire Say?

"Integrating Shellshock AI into our framework has greatly enhanced our asset management capabilities. With Shellshock AI, we've seen marked improvements in visualising pedestrian flows and our Marine traffic patterns, which has been instrumental in optimising the Local Ports asset management strategies. "
Glenelg Shire Council
Team

What Was The Problem?

Glenelg Shire LGA (Local Government Area) needed to capture roadway utilisation data and leverage insights to optimise infrastructure planning, traffic management, and maintenance. The system required the capability to function in various environmental conditions, capable of withstanding various weather conditions and provide real-time data to support decision-making. The system also had to be scalable for future expansions.

What Was The Solution?

Our team developed Shellshock AI, leveraging advanced AI models to analyze pedestrian mobility and utilization in local government areas for a fraction of the cost and effort associated with traditional IoT solutions.

 

Key features of the solution included:

  • AI-Driven Analytics: Utilized sophisticated AI models to analyze data on community engagement and recycling program effectiveness.
  • Durable Hardware: Devices built to withstand extreme weather and environmental conditions, ensuring reliability and longevity.
  • Off-Grid Power Solutions: Integrated solar power systems and battery storage to maintain uninterrupted operation without reliance on mains power.
  • Real-Time Monitoring: Enabled real-time data capture and analysis, providing immediate insights and actionable information to optimize staff schedules and resource allocation.
  • Multi-Parameter Capture: The system can monitor and analyze multiple parameters simultaneously, offering a comprehensive view of community engagement and operational performance.
  • Remote Updates: Capable of changing what parameters it captures through remote software updates, allowing for flexibility and adaptability to evolving needs.
  • Non-Disruptive Deployment: The solution allowed for deployment and data capture without any disruption to traffic flow, as no equipment needed to be installed on the road.

What Was The Outcome?

The AI imaging system for roadway utilisation provided the local council with valuable insights for infrastructure management. Key outcomes included:

 

  • Real-Time Data: Enhanced decision-making with immediate access to roadway utilisation data.
  • Operational Insights: Improved understanding of traffic patterns, aiding in infrastructure planning and traffic management.
  • Proactive Maintenance: Identified maintenance needs promptly, allowing for timely interventions and reduced roadway downtime.
  • Cost Efficiency: Utilized existing camera infrastructure where possible, minimising costs and facilitating rapid deployment.

Want to learn more about Shellshock AI?

See Shellshock AI for yourself by clicking the link below.

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AI System Optimisation

AI System Optimisation

Within just 2 days, SAPHI was able to optimise the throughput of QUBE Logistic’s assets by 7 times without adding any additional infrastructure.

What Was The Problem?

QUBE Logistics was facing significant operational inefficiencies with their large-scale AI system, which was designed to detect defects in vehicles exiting transport ships. The existing system was taking an average of 45 seconds to process each car, resulting in substantial throughput delays and major time inefficiencies. This bottleneck was significantly impacting their ability to maintain a smooth and efficient workflow.

What Was The Solution?

To address these inefficiencies, our team at SAPHI implemented a solution without adding any new infrastructure. This included:

 

  • Asynchronous Processing: Redesigned the system to process images asynchronously, allowing cars to move continuously without stopping.
  • System Integration: Ensured that the new asynchronous processing integrated seamlessly with the existing infrastructure, avoiding any need for additional hardware.
  • Processing Speed: Focused on optimizing existing AI models and processing workflows to achieve significant speed improvements without additional computational resources. The AI algorithms were enhanced to process images 7 times faster.

What Was The Outcome?

The redesigned AI imaging system for Qube delivered exceptional results including:

 

  • Elimination of Downtime: Cars no longer needed to stop for imaging, significantly increasing throughput and operational efficiency.
  • Increased Processing Speed: Processing time was reduced 7-fold within just two days, leading to substantial time savings.
  • Revenue Impact: The efficiency gains generated millions in additional revenue for Qube by speeding up the assessment process and reducing delays.

 

This case demonstrates SAPHI’s ability to dramatically improve operational efficiency and performance using innovative AI solutions without the need for additional infrastructure investments.

 

Do You Have A Project You Need Support With?

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AI Boat Height & Ramp Utilisation

AI Boat Height & Ramp Utilisation

SAPHI developed sophisticated AI models to analyse various boat ramp locations, and provide AI insights for infrastructure management.

What Did LMCC Say?

"Working with SAPHI has provided us with robust, real-time data processing at the source, meeting our privacy requirements and significantly improving our asset optimization and service management capabilities."
Daniel Hartin
Asset Optimisation

What Was The Problem?

Lake Macquarie City Council (LMCC) needed to monitor boat size and ramp utilization across multiple sites to improve infrastructure management and service optimization.

What Was The Solution?

Our team developed sophisticated AI models to capture the number of boats frequenting several major asset locations. The model then calculated boat height in order to categorise boat size. The features of the solution included:

 

 

  • Leveraging Existing Systems: We ensured seamless integration with the existing imaging infrastructure, avoiding the need for new hardware installations. This approach minimised additional costs and simplified the deployment process.
  • Accurate Models: Our AI models were trained to handle diverse environmental conditions including various lighting and weather conditions, ensuring high accuracy. Processes to calibrate the cameras to real-world coordinates were also undertaken, using these to measure the height of the target objects.
  • Scalability: The solution was designed to be easily scalable, allowing for future expansion to additional sites without significant changes.

What Was The Outcome?

The boat ramp utilisation monitoring system provided valuable insights for infrastructure management. Key outcomes included:

 

  • Real-Time Data: Enhanced decision-making with immediate access to utilization data.
  • Operational Insights: Improved understanding of boat ramp usage patterns, aiding in service optimization and proactive maintenance.
  • Cost Efficiency: Leveraging existing infrastructure minimized costs and facilitated rapid deployment.

Do You Have A Project You Need Support With?

Reach out to our friendly team today for a free consultation about your unique project.

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Urban Insights Using AI

Urban Insights Using AI

SAPHI designed an edge AI imaging system for local government to capture and process data, providing valuable insights for infrastructure management.

What Did LMCC Say?

"Working with SAPHI has provided us with robust, real-time data processing at the source, meeting our privacy requirements and significantly improving our asset optimization and service management capabilities."
Daniel Hartin
Asset Optimisation

What Was The Problem?

Lake Macquarie City Council (LMCC) faced the challenge of capturing extensive urban data to support infrastructure upgrades, service management, optimization, and proactive maintenance. Given the vast areas they needed to cover and budget constraints, they required a versatile solution capable of capturing multiple data sources and being reused across different projects. Additionally, the system had to withstand harsh environmental conditions and operate independently without access to mains power.

What Was The Solution?

Our team developed Shellshock AI. Shellshock AI leverages advanced AI models to analyze urban mobility and space utilization for a fraction of the cost and effort associated with traditional IoT solutions. 

 

Key features of the solution included:

  • AI-Driven Analytics: Utilized sophisticated AI models to analyze data on community engagement and recycling program effectiveness.
  • Durable Hardware: Devices built to withstand extreme weather and environmental conditions, ensuring reliability and longevity.
  • Off-Grid Power Solutions: Integrated solar power systems and battery storage to maintain uninterrupted operation without reliance on mains power.
  • Real-Time Monitoring: Enabled real-time data capture and analysis, providing immediate insights and actionable information to optimize staff schedules and resource allocation.
  • Multi-Parameter Capture: The system can monitor and analyze multiple parameters simultaneously, offering a comprehensive view of community engagement and operational performance.
  • Remote Updates: Capable of changing what parameters it captures through remote software updates, allowing for flexibility and adaptability to evolving needs.

What Was The Outcome?

The edge AI imaging system for LMCC provided valuable insights for infrastructure management and proactive maintenance. Key outcomes included:

 

  • Real-Time Data: Enhanced decision-making with immediate access to utilisation data.
  • Operational Insights: Improved understanding of usage patterns, aiding in the optimisation of public space and infrastructure planning.
  • Cost Efficiency: Leveraging existing infrastructure minimised costs and facilitated rapid deployment.
  • Improved Maintenance Scheduling: The data gathered allowed for more accurate and efficient maintenance scheduling, reducing downtime and improving safety.
  • Utilisation Assessments: The insights gained from the monitoring system enabled better assessments of jetty utilisation, supporting resource allocation and planning.
  • Improved Tourism Planning: By understanding the patterns of jetty usage, the LGA could enhance tourism planning, ensuring that the jetties remain a major tourist and economic asset.

Want to learn more about Shellshock AI?

See Shellshock AI for yourself by clicking the link below.

Interested in other projects?

Check out more projects below!

CONTACT

WORKING HOURS

AI Traffic System

AI Traffic System

SAPHI developed a scalable smart city AI traffic system (Shellshock AI) that monitors cars, people, bikes and scooters to inform local infrastructure upgrades without traffic disruption.

Traffic Movement

What Was The Problem?

Local governments need high-quality data to make informed decisions about upgrading infrastructure, installing wayfinding infrastructure and supporting local businesses. Current methods of capturing this data often require the configuration, deployment and management of hundreds of thousands of dollars worth of IoT devices with a high margin of error.

What Was The Solution?

Our team developed Shellshock AI, leveraging advanced AI models to analyze pedestrian mobility and utilization in local government areas for a fraction of the cost and effort associated with traditional IoT solutions.

 

Key features of the solution included:

  • AI-Driven Analytics: Utilized sophisticated AI models to analyze data on community engagement and recycling program effectiveness.
  • Durable Hardware: Devices built to withstand extreme weather and environmental conditions, ensuring reliability and longevity.
  • Off-Grid Power Solutions: Integrated solar power systems and battery storage to maintain uninterrupted operation without reliance on mains power.
  • Real-Time Monitoring: Enabled real-time data capture and analysis, providing immediate insights and actionable information to optimize staff schedules and resource allocation.
  • Multi-Parameter Capture: The system can monitor and analyze multiple parameters simultaneously, offering a comprehensive view of community engagement and operational performance.
  • Remote Updates: Capable of changing what parameters it captures through remote software updates, allowing for flexibility and adaptability to evolving needs.
  • Non-Disruptive Deployment: The solution allowed for deployment and data capture without any disruption to traffic flow, as no equipment needed to be installed on the road.

What Was The Outcome?

The AI imaging system for roadway utilisation provided the local council with valuable insights for infrastructure management. Key outcomes included:

 

  • Real-Time Data: Enhanced decision-making with immediate access to roadway utilisation data.
  • Operational Insights: Improved understanding of traffic patterns, aiding in infrastructure planning and traffic management.
  • Proactive Maintenance: Identified maintenance needs promptly, allowing for timely interventions and reduced roadway downtime.
  • Cost Efficiency: Utilized existing camera infrastructure where possible, minimising costs and facilitating rapid deployment.

Want to learn more about Shellshock AI?

See Shellshock AI for yourself by clicking the link below.

CONTACT

WORKING HOURS

Crop Yield Tracking Using AI

Crop Yield Tracking Using AI

SAPHI revolutionized the approach to crop management for a prominent agriculture business. Harnessing AI-driven analytics, we optimized crop yield tracking, resulting in data-informed farming strategies and increased harvest outputs.

Water protection

What Was The Problem?

In the realm of agriculture, accurate crop yield tracking is indispensable for planning and optimising harvests. However, traditional methods proved unreliable and lacked precision. The extant system faced challenges in predicting and managing yields, leading to missed opportunities and potential financial losses. With the pressing demands of a growing population and fluctuating market dynamics, there was an urgent necessity to transition to a more advanced, data-driven approach for efficient crop management.

What Was The Solution?

To address the crop yield challenges, SAPHI introduced an avant-garde AI-driven solution specifically crafted for crop monitoring. This system meticulously captured the vital details of crop growth and health using machine vision techniques. It analysed parameters such as plant height, colour variations, and other vital signs, ensuring a precise yield forecast. Utilising advanced AI algorithms, the solution identified potential issues, from pest infestations to suboptimal growth conditions. By integrating this solution, farms could make informed decisions without intruding on the natural growth process, ultimately ensuring maximised harvests.

What Were The Outcomes?

  • Significant cost reductions by sidestepping
  • Maintenance overheads were notably diminished.
  • Elevated crop monitoring through detailed AI-driven analytics.
  • High-fidelity data acquisition pivotal for accurate yield forecasts.
  • Tangible reduction in agricultural inefficiencies.
  • Swift insights into crop health and potential issues.
  • Enhanced farm operations with data-centric decision-making strategies.

What Skills Did SAPHI Use To Implement The Solution?

To realize the AI-powered crop yield tracking solution, SAPHI harnessed the collective knowledge of our interdisciplinary team of computer, electrical, and software engineers. The project leveraged a broad spectrum of our core competencies:

  • Embedded microcontroller programming 
  • Creation of robust and encrypted data communication channels.
  • Integration with specialised agricultural sensors and imaging systems.
  • Comprehensive data analytics tailored for agronomic insights.
  • Development and calibration of bespoke AI models for crop analysis.

What Support Did SAPHI Offer After Completion?

SAPHI provides customised packages to support the full system development life cycle and implementation of upgrades to support the evolving needs of our clients and their customers.

 

Do You Have A Project You Need Support With?

Reach out to our friendly team today for a free consultation about your unique project.

Interested in other projects?

Check out more projects below!

CONTACT

WORKING HOURS