Title

HPD: Human Proximity Device

Lead Author Major

Computer Engineering

Lead Author Status

Senior

Second Author Major

Computer Engineering

Second Author Status

Senior

Third Author Major

Computer Science

Third Author Status

Senior

Fourth Author Major

Electrical Engineering

Fourth Author Status

Senior

Fifth Author Major

Computer Science

Fifth Author Status

Senior

Sixth Author Major

Computer Science

Sixth Author Status

Senior

Format

SOECS Senior Project

Faculty Mentor Name

Rahim Khoie

Faculty Mentor Department

Electrical and Computer Engineering

Abstract/Artist Statement

With the progressive nature and growing capabilities of sensor technologies, and their increasing commercial availability, developing more affordable, modular, and increasingly smaller devices for real-world applications has become more common now than ever. Considering the recent Coronavirus pandemic, the importance of discerning the number of human individuals within a given enclosed space has become more pronounced for personal safety. Our research into developing a device that counts the number of unique human interactions within an adjustable proximity aims to combine concise and comprehensible statistics, efficient sensor power management, and portability to allow user interactions to be tracked in a set location or on the move. Our current implementation uses a combination of Passive Infrared, LiDAR, and Image Processing to collect and process data locally and provide a running total of all unique interactions. Then, at the user’s discretion, the data can be uploaded through Bluetooth to a web application for further data processing. The device is handheld and portable, and after starting its process, it does not need any additional input until the user wants to stop collecting data. Upon the completion of our device and the setup of our application environment, we will solidify our design with the aggregation and interpretation of our image segmentation and lidar proximity data to report on our phone app as a future feature update.

Location

School of Engineering & Computer Science

Start Date

7-5-2022 2:30 PM

End Date

7-5-2022 4:00 PM

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May 7th, 2:30 PM May 7th, 4:00 PM

HPD: Human Proximity Device

School of Engineering & Computer Science

With the progressive nature and growing capabilities of sensor technologies, and their increasing commercial availability, developing more affordable, modular, and increasingly smaller devices for real-world applications has become more common now than ever. Considering the recent Coronavirus pandemic, the importance of discerning the number of human individuals within a given enclosed space has become more pronounced for personal safety. Our research into developing a device that counts the number of unique human interactions within an adjustable proximity aims to combine concise and comprehensible statistics, efficient sensor power management, and portability to allow user interactions to be tracked in a set location or on the move. Our current implementation uses a combination of Passive Infrared, LiDAR, and Image Processing to collect and process data locally and provide a running total of all unique interactions. Then, at the user’s discretion, the data can be uploaded through Bluetooth to a web application for further data processing. The device is handheld and portable, and after starting its process, it does not need any additional input until the user wants to stop collecting data. Upon the completion of our device and the setup of our application environment, we will solidify our design with the aggregation and interpretation of our image segmentation and lidar proximity data to report on our phone app as a future feature update.