Abstract
This research considered several applications of a coupled Internet of Things sensor network with Edge Computing (IoTEC) for improved environmental monitoring. Two pilot applications, covering environmental monitoring of vapor intrusion and system performance of wastewater-based algae cultivation, were designed to compare data latency, energy consumption, and economic cost between the IoTEC approach and the conventional sensor monitoring method. The results show that the IoTEC monitoring approach, compared with conventional IoT sensor networks, could significantly reduce data latency by 13%, and the amount of data transmission decreased by an average of 50%. In addition, the IoTEC method can increase the duration of power supply by 130%. Collectively, these improvements could lead to a compelling cost reduction of 55% - 82% per year for monitoring vapor intrusion at five houses, with more houses leading to more significant savings. Additionally, our results demonstrate the feasibility of deploying machine learning tools at edge servers for more advanced data processing and analysis.