This project, developing a Reconfigurable Environmental Intelligence Platform (REIP) aims to alleviate many complex aspects of remote sensing, including sensor node design, software stack implementation, privacy issues, bandwidth, and centralized compute limitations, bringing down start up times from years to weeks. REIP will be a plug-and-play remote sensing infrastructure with advanced edge processing capabilities for in situ- insight generation. Sensor networks have dynamically expanded our ability to monitor and study our world Sensor networks have already deployed specialized sensor networks for many applications, including monitoring pedestrian traffic and outdoor noise monitoring and the need for sensing networks keeps increasing as the use cases for sensor networks expands and becomes more complex. Sensors no longer simply record data, they process and transforms it into something useful before sending it to central servers.
At the core of REIP is a set of hardware modules that connect together to form a sensing solution. Each sensing module will come in a number of variants allowing the user to find the proper tradeoff between complexity/ ost and power/features. The REIP infrastructure will expand the use of audio-visual sensing architectures beyond the highly specialized research groups that are able to design, build, and purchase all the necessary components and make it available to a wider community as a research infrastructure. REIP will be tested on real-world applications, including observation, integrated sensing transportation networks, and indoor sensing for reducing waste in HVAC (Heating, Ventilating, and Air Conditioning) systems. Experts will be able to customize each application domain.
Led by a team of researchers with expertise in sensor networks, machine learning, deep learning, visualization, data analysis, human computing interface, engineering, and occupational therapy, this work will contribute to a variety of projects and is bound to have significant broader impacts. REIP and this research will directly impact a diverse population of students and foster education in science, technology, engineering, and math (STEM). Mentoring opportunities will be provided for all the involved graduate and undergraduate students