This project aims to advance state-of-the-art vehicle safety and smart-home environments by integrating machine learning, telematics, and behavioral analysis with personalized interactive experiences that improve everyday life in challenging environments. In collaboration with insurance industry experts, we plan to design and develop innovative solutions to enhance on-road and property safety, reduce accidents, and improve human safety-related behaviors that create safer communities.
We aim to enhance safety through behavioral insights via technological innovation within the transportation and multi-family housing (e.g., apartments) industries.
- Develop Behavioral Interaction Systems: Utilizing, but not limited to, machine learning/AI, telematics, safety technologies to provide immediate behavioral feedback to user base. This system aims to improve behavior in real-time, leading to safer operating practices.
- Create Safety Modeling: Through the examination of historical and live data sets, we will identify key attributes to safety issues like human, environmental, and other external influences. This analysis will enable us to develop targeted strategies to mitigate these risks.
- Technology and Hardware Development: Explore new technological avenues and hardware solutions to enhance driver safety. This might include advanced driver-assistance systems (ADAS), dash-camera, blockchain, and other innovative tools that can be incorporated into vehicle fleets and/or properties.
- Collaboration with Insurance Experts: Partner with insurance industry professionals who have extensive experience with transportation fleets across the United States. This collaboration will provide valuable insights into the practical applications of our solutions in the context of auto insurance.
Methods:
- Out-of-the-Box Thinking: Required to embrace innovative and unconventional ideas in our approach to solving safety challenges. This involves exploring novel technologies, rethinking existing safety paradigms, and engaging in creative problem-solving to develop solutions that are not only effective but also revolutionary in their design and application.
- Cross-Sector Data Integration: Analyze data from both transportation and residential sectors to understand behavioral patterns and risk factors. This includes extensive data sets from diverse sources, including telematics, federal government data, and insurance records.
- Machine Learning Implementation: Develop and refine machine learning models to interpret the data, focusing on identifying behaviors and suggesting corrective actions.
- Prototype Development: Design and test prototypes of the proposed systems and hardware, ensuring they are effective, user-friendly, and applicable in real-world scenarios.
- Stakeholder Engagement: Regularly engage with insurance, business executives and industry professionals to align our solutions with industry needs and integrate expert feedback into our development process.
IMPACT:
This project stands to make significant contributions to public well-being by enhancing safety and reducing costs. Leveraging technology and data, this project aspires to create a safer living and traveling environment, thus reducing the financial impact of these issues. The anticipated outcomes are manifold: a decrease in road and residential accidents, diminished property losses, fewer litigation cases, and a substantial enhancement in public safety and well-being. This initiative not only aims to protect lives but also to alleviate the economic strain these incidents place on society.
Please send a email to: win@arizona.edu for more information on how to apply.