Towards a Smart Data Transmission Strategy for IoT Monitoring Systems: Application to Air Quality Monitoring

Abstract

In the modern digital area, Internet of Things (IoT) is increasingly gathering attention for the implementation of applications in several aspects of everyday activities, intending to make our cities smarter and more comfortable. Therefore, the implementation of these IoT applications raises several challenges to overcome. One of these challenges is the efficient use of resources at each stage of the application, such as acquisition, storage, processing, and networking. In smart cities, many IoT monitoring systems continuously generate large amounts of data. These data volumes, before they can be processed and responded, must first be transmitted through the city's networks (Wifi, Bluetooth, LTE). To deal with this considerable amount of continually transmitted data and to reduce the load on networks, we propose an approach based on the efficient use of data compression in IoT systems. This approach uses a data compression smart strategy to reduce the transmitted data during the acquisition process and thus minimize the use of network resources while providing the user with relevant information in real-time using a prioritization mechanism. In order to show the efficiency of our proposal, we conducted experiments on a case study of an air quality monitoring system