While AI for driver behavior holds great promise in enhancing road safety and promoting responsible driving, a successful deployment is more like a marathon than it is a sprint.
By Don Diego Padilla II

You cannot read a business periodical or listen to the financial news without hearing about the emerging technology trend of Artificial Intelligence (AI). More and more industries are looking to machine learning solutions, robotics, and predictive analytics to enhance their business. Among these is onboard AI solutions that have the potential to positively impact multiple verticals in the Waste and Recycling industry. The most significant impact involves increased safety initiatives relating to driver behavior. Additional notable impacts are improved efficiency and the environmental impact on waste management operations.


Safe Fleet MOBILEMULETM AI, AI-Powered Dual Dash Cam. Images courtesy of Safe Fleet.

Driver Behavior
AI for driver behavior refers to the use of artificial intelligence technologies to monitor, analyze, and improve the behavior of drivers on the road. AI systems for driver behavior typically use various sensors and data sources to collect intelligence about the driver, the vehicle, and the surrounding environment. Common data sources include GPS, accelerometers, cameras, and onboard diagnostic systems coupled with biometrics readings from the driver. The typical system will track about 13 different biometrics to detect and analyze the driver’s behavior. Among these are head yaw, pitch, roll, X and Y positions, eye aperture right, left, horizontal, and vertical gaze, blink, voice activity, audio, and drowsiness levels. In the interest of addressing privacy concerns, some systems have the ability to redact the images so that drivers cannot be shadowed in real-time and the only recordings available are those generated from the system upon detecting incidents.

All this data combined with AI machine learning algorithms create a solution designed to enhance safety, reduce accidents, and promote more responsible driving habits. Here are some ways AI technology is being applied in this context:

1. Driver Monitoring Systems (DMS): AI-powered cameras and sensors can be installed in vehicles to monitor the driver’s behavior in real time. This includes detecting fatigue/drowsiness, distracted driving, smoking, seat belt usage, and phone usage. In addition, these systems can typically detect aggressive driving such as speeding, tailgating, lane departure, rolling stops, hard braking, high-risk vehicles up ahead, and forward collisions. The system can then provide alerts or interventions to bring the driver’s attention back to the road and uses features of bi-directional streaming, a panic button, driver scoring, and cloud services within a back-office portal for video and metadata storage, reporting, and coaching.

2. Driver coaching and training: AI can offer personalized coaching and feedback to drivers based on their performance for enhanced training effectiveness. It can identify areas of improvement, such as harsh braking, speeding, erratic lane changes, and excessive idling, and then provide suggestions to encourage safer driving habits.

3. Accident Prevention: AI can anticipate potential collisions and provide advanced warning systems to drivers to avoid accidents. These warning systems can be visual and/or auditory alerts, haptic feedback, or even automatic braking in certain situations.

4. Insurance and telematics: Some insurance companies encourage the use of AI-powered telematics devices by providing lower premiums when claims experience is improved over time using these systems. Safer driving habits are a win-win for everyone.


Sample Back Office “Trip” events.


Sample Back Office Dashboard screen shot.

Additional areas of focus where onboard AI is impacting our industry are within the enhancement of productivity and efficiency. Data plus analytics equals business intelligence and the automation of analytics that AI provides is dramatically collapsing the time and effort to recognize problematic areas that need improvement. Here are a few examples:

1. Real-time Data and Analytics: AI can collect and analyze real-time data from waste vehicles, such as GPS locations, waste weights, collection times, service verification, and other operational metrics. This data can be used for performance evaluation, resource allocation, and identifying areas for improvement and profit analysis in waste management processes.

2. Automated Service Verification and Contamination Detection: AI technology is being used to automatically identify waste exceptions, including overflows and contamination thereby streamlining the driver’s workflow while more accurately documenting these critical incidents:
• Contamination: Contamination in recycling waste is a chronic issue in waste management due to increased operational costs for MRFs, haulers, and the communities they serve. Historically identifying the source of contamination has been a manual process and very difficult to detect, report, and control. Using an AI onboard video telematics solution with hopper camera(s), haulers can now automatically detect contamination to better control and reduce these incidents. This allows the upload of hopper images/videos that are processed through the AI application on every lift to identify the contamination and tie it directly to the source.
• Exception Detection: With an onboard AI and road-facing camera(s) system exceptions such as overflowing containers can also be automatically detected providing haulers with the ability to document these incidents with photographic/video proof thereby allowing them to accurately invoice and right-size services for clients.

3. Route Optimization: AI can analyze historical data on waste collection routes, traffic patterns, and other variables to optimize the routes taken by waste vehicles. By determining the most efficient paths, AI can reduce fuel consumption, emissions, and overall operational costs.

4. Predictive Maintenance: AI can monitor the condition of waste vehicles and help predict potential maintenance issues before they become critical. By analyzing sensor data and vehicle diagnostics, the onboard system can be integrated with back-office maintenance solutions to schedule maintenance and prevent breakdowns, ensuring that the fleet is operational and minimizing downtime.

5. Autonomous Waste Vehicles: As autonomous vehicle technology advances, AI can be applied to enable waste vehicles to operate autonomously in controlled environments, such as closed waste collection sites or industrial complexes. This can increase efficiency and reduce the need for human intervention in specific waste management tasks.


Samples of Contamination Detection


Sample of Eye Aperture detection.



Sample of AI DashCam.

In closing, if you have not already deployed some of these solutions, I would encourage you to investigate them as there is tremendous potential for improvement with the adoption of onboard AI. However, I also want to point out that there is an important ethical aspect one needs to consider before deploying onboard AI solutions, specifically for driver behavior. While AI for driver behavior holds great promise in enhancing road safety and promoting responsible driving, it is important to consider potential ethical implications, user acceptance, and ongoing improvements in the technology to achieve the desired outcomes effectively. Do your homework and remember, like all technology, a successful deployment is more like a marathon than it is a sprint. | WA

A waste industry fleet management veteran, Don Diego Padilla II is Vice President of Sales at Safe Fleet Waste & Recycling, where he spearheads business and customer development activities. Safe Fleet is the largest fleet video supplier in North America with more than six leading video surveillance brands and associated integrated fleet safety management technologies designed to help cities work smarter and stay safer. Previously, Don Diego held the role of Regional Sales Director for Allied Waste (Republic Services), a leading provider of solid waste collection, transfer, recycling, and disposal services in the U.S. His industry white paper on fleet safety garnered a Network Products Guide Award in the “Best White Paper” category. He has been published in numerous industry magazines and is a frequent speaker at industry forums and regional municipal waste management events. Don Diego can be reached at (877) 630-7366 or e-mail [email protected]

Safe Fleet Waste & Recycling (SFWR) is an award-winning, technology leader of connected “smart truck” solutions for waste management fleets. Safe Fleet is a leading provider of video and safety solutions for fleets throughout North America and has more than 20 years of experience developing the most advanced fleet management, mobile, and software solutions designed for waste and recycling collection environments. Safe Fleet systems are installed in thousands of vehicles across North America. Products enable the industry’s top fleets to link their drivers and vehicles to business operations in real-time to ensure optimal productivity, safety, sustainability, profitability, and customer service. For more information, call (877) 630-7366, e-mail [email protected], or visit www.safefleet.net.