A Low-Cost and Energy Autonomous IoT Framework for Environmental Monitoring

Abstract

The emergence of IoT devices that support sensor technology has gain much attention for their integration into smart city applications to improve citizens’ quality of life. In industrial territories, people that suffer from chronic respiratory diseases, e.g., chronic obstructive pulmonary disease, asthma, occupational lung diseases and pulmonary hypertension require special care, targeted information and efficient treatment, when the environment deteriorates their condition. This article presents the design of an IoT framework that wirelessly connects devices of low-cost, low-power consumption and integrates multi-sensor measurement capabilities (CO2 concentration, humidity, temperature, particulate matters concentrations) with an open-source IoT platform aiming to alert the aforementioned population, when the combination of aerial pollution and weather conditions severe impact their daily activities. The energy autonomy of the IoT devices that are connected via wireless sensor network is explored and utilized. Finally, we evaluate the functionality and the accuracy of the low-cost sensors and demonstrate how proper filtering can improve their performance and mitigate problems stemming from outage times. For the latter, we have evaluate the effectiveness of forecasting algorithms like ARIMAX, LSTM and PROPHET on the measurement data.