Abstract:
The mangroves are delicate biodiverse ecosystem not only provide habitat for numerous organisms but also contributes to our economy and other resources needed to livelihood of local communities. Pollutions carried by the rivers such as fertilizers, pesticides, oils and other toxic man-made chemicals kills the fauna and flora in the mangrove. Herein, an IoT system based on the Mangrove Quality Index (MQI), focusing on hydrology index will be adopted to monitor mangrove health in real time and provide important data to scientist to quickly find solutions to rectify disturbances. The system is also developed to enable effective mitigation measures to the mangroves resource sustainability. The system consists of node stations using various sensors, reliable communications, lightweight edge server by utilizing Docker, with machine learning and visual analytics. By adopting open source technologies, the system able to be deployed faster and with lower cost. It will monitor water quality with parameters such as Dissolve Oxygen, salinity, temperature, pH, precipitation, water level, turbidity, ammonia level and electrical conductivity. Each station will be equipped with sensors that relay the information in real time 24/7. The system developed enable significant real time monitoring and effective intervention to manage and sustain the ecosystem. This research will also analyze the effectiveness of edge computing by imparting machine learning algorithms into low power and low memory microcontroller units. With edge computing the higher capability nodes will reduce bandwidth consumption and cloud processing requirements. The system includes mobile notification and visual analytics with machine learning capabilities to classify the MQI. By implementing this system, the mangrove ecosystem will be effectively monitored and prompt action can be taken when declining MQI values are detected.
Recent Comments