IoT-Based Air Quality Management in Somalia

Air pollution in Somalia is a serious threat to human health, agriculture, and the environment and requires immediate
attention. The DSM501A PM2.5 sensor, Raspberry Pi, IoT, and cloud computing are all used in this study to create a
comprehensive air quality monitoring system. The system’s architecture allows for measuring particulate matter and
environmental characteristics, allowing for a more comprehensive approach to pollution management. The study highlights the efficiency of merging IoT and cloud computing for real-time data gathering, processing, and display by exploiting the versatility of the Raspberry Pi. The created approach fills a critical gap in existing monitoring frameworks by focusing on particulate matter. It stresses the importance of public awareness and international engagement in mitigating air pollution in Somalia. The suggested system is suited for deployment in various geographic and economic scenarios due to key aspects such as cost, energy efficiency, and scalability. In the midst of worldwide air quality challenges, the findings highlight the relevance of data-driven solutions in protecting human health, promoting environmental sustainability, and boosting community well-being. This study
advances air quality monitoring methods and calls for comprehensive air pollution control tactics in Somalia.