Research Article
Context-Aware Indoor Environment Monitoring and Plant Prediction Using Wireless Sensor Network
@INPROCEEDINGS{10.1007/978-3-030-23943-5_11, author={Sadia Mughal and Fahad Razaque and Mukesh Malani and Muhammad Hassan and Saqib Hussain and Ahsan Nazir}, title={Context-Aware Indoor Environment Monitoring and Plant Prediction Using Wireless Sensor Network}, proceedings={Emerging Technologies in Computing. Second International Conference, iCETiC 2019, London, UK, August 19--20, 2019, Proceedings}, proceedings_a={ICETIC}, year={2019}, month={7}, keywords={Pervasive Context-aware Wireless sensor networks (WSN) Remote sensor Acquisition Reasoning Schema Node Air quality monitoring (AQM)}, doi={10.1007/978-3-030-23943-5_11} }- Sadia Mughal
Fahad Razaque
Mukesh Malani
Muhammad Hassan
Saqib Hussain
Ahsan Nazir
Year: 2019
Context-Aware Indoor Environment Monitoring and Plant Prediction Using Wireless Sensor Network
ICETIC
Springer
DOI: 10.1007/978-3-030-23943-5_11
Abstract
Remote sensor networks are a flexible innovation that deals the capacity to observe thorough actual occurrences as well as a wide-range environment where physical frameworks are considered unsuitable and costly. This study presents the context-aware based remote sensing network (remote or wireless sensor networks or WSN uses alternatively in this paper) for indoor ecological observing at home. Indoor environs atmosphere as well as stability among occupant’s well-being and predicting plants are the principles of this proposed framework. The introduced framework comprises of various sensor gadgets simultaneously evaluating temperature, relative humidity via mobile sensors, illumination, carbon dioxide CO, oxygen O and benzene CH levels in separate spaces. This study also exhibits the framework structure, the context-aware lifecycle and the context modeling and reasoning architectures for observing the environment.
