Mathew Jarvis

Basic Information

Applicant Type: Individual/s

Key Contact: Mathew Jarvis

Main Questions

Problem Solution

Lithium-ion batteries are increasingly ending up in household bins, often still inside electronics, tools, or toys. Hidden under bags of rubbish, they’re hard to detect and easy to miss. Once compacted inside a garbage truck, these batteries can ignite, starting fires that pose serious risks to drivers, damage equipment, and shut down waste facilities.

NRG Sense addresses this issue at the point of collection, before the bin is lifted or the waste enters the vehicle.
Our system uses AI-based detection to scan each bin in real time. If a likely battery is identified, the driver is alerted, and the bin can be put aside for safe handling. This stops the battery from being loaded into the truck or transported to a waste depot, where it could ignite.

The system is designed to be practical for everyday operations. It works quickly, mounts onto existing trucks, and requires minimal setup. The focus is on reducing risk at the frontline and protecting both driver and community safety.

Impact

NRG Sense helps reduce the risk of lithium-ion battery fires in waste collection, a growing safety and operational issue across Queensland. The system is designed to make an immediate, measurable difference in routine waste operations.

Key areas of impact:

Driver Safety:
- Fires inside trucks are unpredictable and dangerous. Detecting batteries before they’re tipped into the vehicle reduces this frontline risk.

Community Safety:
- Fires that spread beyond trucks can threaten nearby homes, facilities, and workers. Early detection helps mitigate these broader risks.

Fleet and Facility Protection:
- Preventing a fire means avoiding expensive truck write-offs and infrastructure damage. This protects public assets and reduces downtime.

Recycling Continuity:
- Fires at material recovery facilities often contaminate recyclables and halt operations. Stopping batteries at the bin level helps maintain smooth, continuous recycling workflows.

Battery Diversion:
- Early detection gives councils the option to separate batteries and send them to appropriate recycling streams, supporting resource recovery goals.

Deployment at Scale:
- The system is retrofittable and works across a variety of truck types. It’s designed for both metro and regional fleets.

Business Model

NRG Sense is being developed by a founder-led Australian solutions company focused on advancing battery detection, renewable integration, clean tech, and public safety. The business is driven by the need to adapt to changing battery technologies while addressing the safety risks they present across the waste sector.

Model Summary
NRG Sense operates as a hardware-based AI system installed on garbage trucks. The device scans each bin before tipping and alerts the driver if a likely battery is detected. Optionally, a cloud dashboard is available to track incidents and support operational planning. The system can be remotely supported and continually optimized as the AI model improves over time with increased data collection.

How We’ll Reach the Market:
- Start with pilot programs through council partnerships
- Gather results and feedback to refine the product
- Expand based on demand from public and private waste operators

What’s Needed to Launch:
We estimate an initial rollout of 10–15 units would support a full commercial launch. Early deployments would also help refine training materials and procedures for operators.

Market Readiness

Technology Readiness Level (TRL): TRL 5 – technology validated in a relevant environment.

Completed Work:
- Built and tested a working prototype
- Verified detection logic using real bin materials
- Simulated lift cycles in controlled conditions

Next Steps:
- Improve durability for truck environments
- Deploy on live trucks in pilot programs
- Adjust detection performance based on local waste types

Timeline Estimate:

Finalising MVP
8–10 weeks

Pilot coordination
8 weeks

Pilot execution
6–8 weeks

Post-pilot updates
4 weeks

Pilot Scope:
Deploy to 3–5 trucks
Monitor 1000+ bin lifts
Evaluate detection accuracy and false positives

Deployment Requirements:
8 weeks’ notice to set up pilot
Pilot run of approx. 2 months
Commercial rollout within 6 months of completion

The product is designed for real-world use and minimal disruption. With support, we can move quickly into trials and scaled deployment.

Team

Founder: Mat Jarvis

Mat has worked in electrical systems, manufacturing, and operational delivery for over 15 years. He has led technical operations for safety camera systems — including vehicle-mounted tech, field support, and lean production.
He’s used to working in regulated environments and getting new hardware into the field.

He has a strong understanding of lithium battery safety and the operational challenges involved in battery handling, having led teams responsible for high-reliability hardware systems in the field.

Project Team:
- Engineering partners for electronics and AI model development
- Design contractors for enclosures and mounting systems
- Software consultants for the optional cloud dashboard
- Field support for installation and training

Experience with Project Delivery:
- Previously managed deployments with multiple government clients
- Built operational systems used across Australia
- Familiar with working under compliance and safety requirements

Industry Partnerships
NRG Sense is actively speaking with:
- Councils for pilot projects
- Fire safety experts to refine driver procedures
- Circular economy partners for end-of-life battery handling

We’re set up to move quickly, execute pilots, and scale responsibly with local partners.