Data Reduction Techniques in Wireless Sensor Networks with AI
- Title
- Data Reduction Techniques in Wireless Sensor Networks with AI
- Creator
- Arora G.D.; Chopra N.K.; Gopinath N.; Ravichandran S.K.; Chakravarthi M.K.; Gangodkar D.
- Description
- Due to their numerous uses in practically every part of life and their related problems, such as energy saving, a longer life cycle, and better resource usage, the research of wireless sensor networks is ongoing. Its extensive use successfully saves and processes a considerable volume of sensor data. Since the sensor nodes are frequently placed in challenging locations where less expensive resources are required for data collection and processing, this presents a new difficulty. One method for minimizing the quantity of sensor data is data reduction. A review of data reduction methods has been provided in this publication. The different data reduction approaches that have been put forth over the years have been examined, along with their advantages and disadvantages, ways in which they can be helpful, and whether or not using them in contexts with limited resources is worthwhile. 2022 IEEE.
- Source
- Proceedings of 5th International Conference on Contemporary Computing and Informatics, IC3I 2022, pp. 48-51.
- Date
- 2022-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- AI; data fusion; data integration; data reduction; the Internet of Things; Wireless sensor networks
- Coverage
- Arora G.D., Vardhaman College of Engineering, Department of Artificial Intelligence (AI) and Machine Learning (ML), Hyderabad, India; Chopra N.K., Chandigarh Engineering College, Department of CSE, Mohali, Punjab, Landran, India; Gopinath N., Sri Sairam Engineering College, Department of Computer Science and Engineering, Tamil Nadu, Chennai, India; Ravichandran S.K., Christ University, Department of Computer Science and Engineering, Karnataka, Bangalore, India; Chakravarthi M.K., VIT-AP University, School of Electronics Engineering, Andhra Pradesh, Amravati, India; Gangodkar D., Graphic Era Deemed to Be University, Department of Computer Science & Engineering, Uttarakhand, Dehradun, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835039826-7
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Arora G.D.; Chopra N.K.; Gopinath N.; Ravichandran S.K.; Chakravarthi M.K.; Gangodkar D., “Data Reduction Techniques in Wireless Sensor Networks with AI,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 27, 2025, https://archives.christuniversity.in/items/show/20108.