Information Processing in IoT Based Manufacturing Monitoring System

Abstract

The Internet of Things (IoT) is used widely in health care, manufacturing, industry, smart homes, and smart cities, among other areas. The data is collected in the IoT environment by placing the sensors in a structured way in a specific area. It collects data in accordance with the defined service for devices of IoT. For optimal handling of massive data in an IoT environment, the study work provided a new processing information in IoT centered factory system of monitoring. Data management is a critical and necessary activity in IoT systems, and present solutions of big data-centered are sufficient to satisfy every requirement. In the IoT Big data context, it's critical to increase data handling performance because most systems are solely designed for real-time data collecting. The proposed strategy utilizes Hadoop and Apache Kafka to meet the need for real-time data collection as well as offline processing. In comparison to the clustering model of traditional hierarchical and the neural network of back propagation model, the approach proposed performs well in data management and information extraction.