Brandon Stephen Good

Occupancy and Activity Monitoring with Doppler Sensing and Edge Analytics: Demo Abstract

We demonstrate an occupancy detection and human activity monitoring system using low-cost motion sensing, edge computing and wireless networking devices. We design a dual Doppler sensor to achieve high signal sensitivity and wide sensing range. We develop signal filtering, detection and machine learning algorithms on an embedded computer to generate classification result in real-time. We also implement web services to enable users to access signal and room state via a wireless network. Compared with conventional occupancy sensors, the dual Doppler system has higher detection rate, and also has the capability of detecting activities even for multiple people.

RFID for air cargo operations: return on investment analysis through process modeling and simulation

In the airline industry, radio frequency identification (RFID) can enhance profitability of cargo operations by improving asset utilization and reducing system inefficiencies. However, the adoption of such technology is hindered by costs of infrastructure, hardware and software development, and integration. In order to analyze the return on investment (ROI) from an RFID solution, this paper describes an approach to predict process improvement from the RFID implementation using discrete event simulation. The simulation measures improvements in decreasing processing times and required resources through a comparison analysis of the “as-is” system and the “to-be” RFID enabled system. The metrics are then used as inputs to the ROI calculation. A complete ROI analysis for RFID feasibility in the studied air cargo terminal is also presented.