Sensors are becoming ubiquitous. From almost any type of industrial applications to intelligent vehicles, smart city applications, and healthcare applications, we see a steady growth of the usage of various types of sensors. The rate of increase in the amount of data produced by these sensors is much more dramatic since sensors usually continuously produce data. It becomes crucial for these data to be stored for future reference and to be analyzed for finding valuable information, such as fault diagnosis information. In this paper we describe a scalable and distributed architecture for sensor data collection, storage, and analysis. The system uses several open source technologies and runs on a cluster of virtual servers. We use GPS sensors as data source and run machine-learning algorithms for data analysis. 2.1. Sensors, Internet of Things, and NoSQL. Sensors are everywhere and the size and variety of the data they produce are growing rapidly. Consecutively, new concepts are emerging as the types and usage of sensors expands steadily.
The architecture for a distributed sensor data collection, storage, and analysis system developed using Hadoop in a cloud environment is presented in REF .
Architecture and Implementation of a Scalable Sensor Data Storage and Analysis System Using Cloud Computing and Big Data Technologies
Journal of Sensors
Journal of Sensors
Computer Science