Published Paper Details:

The advanced systems based on the wireless sensor network, artificial intelligence and the eco-system of the communication protocols provides possibilities of building more efficient, robust and flexible system for the urban environment monitoring. The exacting and obstinate constraints of the communication channel have various limitations of the real-time monitoring based on the network performance of the data delivery through the wireless sensor network deployments in the urban environment. These challenges can be handled by the use of the smart ad intelligent system using predictive modeler by incorporating the machine learning aspects of the artificial intelligence by means of behavioral study of the historical data of the environment conditions in the urban context. Another critical challenge is that the deployment strategy for specific application demands a customized architecture of the wireless sensor network setup. To alleviate this challenge, this paper basically provides a generalized architecture design approach for the urban environment monitoring with the use-case study on the air quality dataset, water quality dataset, urban power usage dataset and storm risk prediction dataset so that the innovative solution approach becomes adaptive to the varied application context.