Classification Extension based on IoT-Big Data Analytic for Smart Environment Monitoring and Analytic in Real-time System

Abstract

Monitoring water conditions in real-time is a critical mission to preserve the water ecosystem in maritime and archipelagic countries, such as Indonesia that is relying on the wealth of water resources. To integrate the water monitoring system into the big data technology for realtime analysis, we have engaged in the ongoing project named SEMAR (Smart Environment Monitoring and Analytic in Real-time system), which provides the IoT-Big Data platform for water monitoring. However, SEMAR does not have an analytical system yet. This paper proposes the analytical system for water quality classification using Pollution Index method, which is an extension of SEMAR. Besides, the communication protocol is updated from REST to MQTT. Furthermore, the real-time user interface is implemented for visualisation. The evaluations confirmed that the data analytic function adopting the linear SVM and Decision Tree algorithms achieves more than 90% for the estimation accuracy with 0.019075 for the MSE.

Effect of node centrality for IoT device selection in opportunistic networks: A comparison study

“…A large number of Internet‐connected machines will generate and exchange an enormous amount of data that make daily life more convenient, help make a tough decision, and provide beneficial services. The IoT probably becomes one of the most popular networking concepts that has the potential to bring out many benefits …”