A Semantic Notification Approach for IoT-Based Sensory Data

Abstract

Internet of Things (IoT) sensors is becoming commonplace in people's daily life. Even, many cities have already deployed a very large number of IoT sensors toward the smart city initiative. However, lack of semantics in the presentation of IoT-based sensory data poses the perception complexity by general people. Adding semantics to the IoT sensory data remains a challenge for smart cities. In this paper, we present a prototype implementation that provides meaningful sensory data notifications about environment status for people and authorities. The approach is based on spatio-temporal thresholds that compose of multiple IoT sensors' readings. Our developed IoT sensory data analytics adds real-time semantics to the received sensory data stream by converting the IoT sensory data into meaningful and descriptive notifications about the environment status such as green locations, emergency zone, crowded places, green paths, polluted locations, etc. Our adopted IoT messaging protocol is capable of handling a very large number of dynamically added static and dynamic IoT sensors' publication and subscription processes. People can customize the notifications based on their preference or can subscribe to existing semantic notifications in order to be acknowledged of any concerned environmental condition.