Bagula, AntoineChen, Shu2020-02-192024-10-302020-02-192024-10-302019https://hdl.handle.net/10566/16927>Magister Scientiae - MScAir pollution is becoming a challenging issue in our daily lives due to advanced industrialization. This thesis presents a solution to collection and dissemination of pollution data. Most of the devices that monitor air quality are costly and have limited features. The aim of this study is to revisit the issue of pollution in cities with the aim of providing a cheaper and scalable solution to the challenge of pollution data collection and dissemination. The solution proposed in this paper uses Raspberry Pi and Arduino micro-controller boards as the foundation, combined with specific sensors to facilitate the collection and transfer of pollution data reliably and effectively. While most traditional air pollution monitoring equipment and similar projects use memory cards as a medium for data storage, the system proposed in this research is built around a new network selection model that transfers data to the server by using either Bluetooth, Wi-Fi, GSM, or the LoRa protocol. The connectivity protocol is selected automatically and opportunistically by the network selection algorithm defined in the micro-controller board. The final data will be presented to the user through a mobile application and website interface effectively and intuitively after being processed in the server. This data transfer system can effectively reduce the cost and input of human resources. It is a viable solution. For other environmental research, this system can provide an air quality data support for analysis and reference. Modularity and cost-effectiveness are fully considered when designing the system. It is a viable solution. We can generalize the system by slightly changing the data transmission modules. In other case, it can be used as a platform for similar data transmission and offer help for other research directions.enAir pollutionRaspberry PiArduinoNetworking SelectionIndustrializationSmart cities air pollution monitoring system - Developing a potential data collecting platform based on Raspberry PiUniversity of the Western Cape