Design of a Data Collection System with Data Compression for Small Manufacturers in Industrial IoT Environments

With advance of IoT (Internet of Things) technology, many manufacturers install several sensors to monitor the status of machines and the health of the whole manufacturing process. In addition, the sensed data are usually transmitted to a backend database for further analysis. However, the dramatic volume of data sensed by the sensors causes the problem of huge storage requirement and network traffic for the small medium manufacturers which have limited resource and budget in IT (Information Technology). To deal with this problem, we design a two-layered architecture using compression technique to reduce the network traffic. In addition, we use MongoDB, a NoSQL database, to store the compressed data due to MongoDB's excellent scale-out ability and cost-efficiency. We conduct several experiments to measure the performance of the proposed architecture with several compression methods. Experimental results show that with proper lossless compression method, the reduction ratio of the volume of the data is around 80% at the cost of slight increase in execution time.