Affordable Green IoT-Based System for Remote Sensing of PM1, PM2.5 and PM10 Particulate Matter

Abstract

Particulate matter (PM) possesses the capacity to intrude deeply into the respiratory system, even infiltrating the bloodstream. Prolonged exposure to heightened PM concentrations has been causally associated with a spectrum of respiratory ailments, encompassing asthma, bronchitis, and chronic obstructive pulmonary disease (COPD). This paper endeavours to introduce a remote sensing system tailored for the quantification of particulate matter, underpinned by the principles of the Green Internet of Things (GioT). This framework is rooted in the pursuit of an ecologically harmonious infrastructure and energy sustainability. The devised architecture integrates PM 1, PM 2.5, and PM 10 sensors, seamlessly interfaced with Arduino microcontrollers, thereby facilitating real-time data acquisition. To sustainably energize this system, solar cells are harnessed to furnish a reliable power source. Augmenting this configuration is a data communication infrastructure established upon LoRa (Long Range) technology, a hallmark of the Green Internet of Things. Concomitantly, empirical investigations have been conducted to illuminate system performance. These inquiries were conducted in conditions mirroring low particle deposition scenarios, culminating in an observed average error spectrum spanning 5.64% to 6.95%. Further examinations scrutinized the data transmission process through LoRa, unveiling an impressive maximal transmission range of 281 m while conserving data transmission viability. Additionally, an exploration of energy utilization encompassed both empty and comprehensive data transmissions, divulging a marginal disparity of 0.1 Watt per data transmission event. In the final analysis, the conducted assessments affirm the system's fidelity, disclosing an error quotient below the 10% threshold. Most notably, the discerned operational efficiency of the energy supply substantiates its synergy with sustainable energy paradigms. In summation, this study proffers an innovative remote sensing system, harmonizing the nuanced demands of PM quantification with the virtuous principles of the Green Internet of Things. By merging the acumen of PM sensors, solar-driven power provisions, and the efficiency of LoRa communication, the proposed framework establishes a salient benchmark for integrative sensor networks with ecological resonance.