Fog Computing-Based Environmental Monitoring Using Nordic Thingy: 52 and Raspberry Pi

Abstract

Environmental quality monitoring has become a major concern due to its severe impact on the well-being of living things. A continuous monitoring of environmental status related to air and water quality is essential for real-time analysis and efficient decision-making that could ensure safety and for healthy living standards. For real-time decision-making, we require the processing of streaming data intelligently to avoid latency. The real-time requirements are met by introducing an intermediary fog layer that plays a vital role between the end devices and cloud. This layer collects processes and stores the data at the edge of the network. In the proposed work, use of fog computing is exploited to monitor the environmental remotely monitoring and respond in real time based on the context for decision-making with the available streaming data that allows deriving valuable insights for prediction. The fog computing-based system offers support to provide low latency, real-time insights, decision-making, reliability, reduce the amount of data sent to the cloud, and address some of the weakness of cloud computing. It helps to alert the concerned authorities instantly to take necessary actions. This paper proposes a model on fog-based environmental monitoring and a simple testbed setup using Nordic Thingy: 52 and Raspberry Pi. The Raspberry Pi acts as a fog node and the fog services could be further exploited to realize its benefits.