Abstract
This chapter presents a novel cloud‐based approach to the problem in air quality monitoring. This approach can be easily extended to other types of environmental monitoring in smart cities. The chapter guides readers through the design of two sensor front ends ‐ a stationary air quality sensor that connects to the cloud via Ethernet and GPRS and a portable sensor that connects to the smartphone via Bluetooth 4.0. It also describes the design of APIs, interfaces, and web services for the third‐party developers to create applications on top of this systems. The chapter further introduces a combination of data analysis and machine learning techniques for signal conditioning, sensor calibration, and inference. A novel client‐cloud system, called AirCloud, is used to address the numerous challenges in city‐scale air quality monitoring that is both accurate and affordable. AirCloud uses a heterogeneous set of data sources as inputs.
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