Abstract
Since Bangladesh is a riverine country, at present, there are 230 rivers flowing through her. Due to the ever-growing number of industries, water pollution in the rivers has become a severe problem in Bangladesh. Almost every river, especially rivers beside the cities are being polluted by the unfiltered wastes discharged by numerous factories. As most of the industries have no proper waste treatment plant, all these wastes and poisonous chemicals are released into the river water causing extreme harm to all lifeforms. Additionally, this type of contamination incites serious public health crises and causes an increasing number of deaths due to waterborne diseases among the people of Bangladesh. Hence, our research proposes a system to remotely monitor the water quality of a river so that the authorities can gather better insights about the condition of that particular river and predict the critical future phenomena. Consequently, they will be able to take auspicious steps in order to protect the rivers and save the environment. The proposed framework can observe the real-time value of pH, conductivity, turbidity, temperature and flow of the water by utilizing various sensors. Furthermore, through our device, effective predictions about imminent floods can be made. Thus, authorities can commence early warning for floods and ensure prompt evacuation. Thus, our technique can significantly minimize the casualties caused by this disaster. In this context, real-time feeds are obtained through Internet of Things (IoT). For wireless data transmission Message Queuing Telemetry Transport (MQTT) is used. Besides that, Long Range Wide Area Network (LoRaWAN) is integrated with the system to act as a backup means for communication when MQTT is not operational. The data is stored in a PostgreSQL database for further processing. Lastly, we have used a popular Python framework-Django for building an interface in an effort to visualize the data procured from the sensors.