• Bhawna Sharma
• Sheetal Gandotra
• Romika Manhas
• Mehreen Choudhary
• Nitika Gupta

The Internet of Things (IoT) is becoming ubiquitous in our everyday lives, implying that more technologies will generate data. Various environmental attributes such as temperature, humidity, light, etc. are monitored using IOT sensors. These sensors produce data periodically and storing this huge amount of data in a database is becoming a huge challenge in the data storage infrastructure. Prior research has proposed compression algorithms and signature techniques to reduce the data storage but they do not specify how the data patterns are defined. Since daily sensing of the environment exhibits similar patterns, data generated is highly redundant .Therefore, this paper, proposes a low storage system that stores data models rather than storing raw data points. Polynomial models are developed that fit a sample data set and then store these data models with the corresponding time periods that captures the behavior of the sensor data. Different polynomial equations are used to generate the data models. Two different strategies are implemented to use these polynomial equations for obtaining data models aiming more accuracy and better computation speed. Any desired value can be obtained using these models.

Internet of things (IoT), sensors, database, data models, wireless sensor network.

"Modeled Sensor Database for IOT Aiming Efficient Data Storage", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.380-389, June-2019, Available :http://www.jetir.org/papers/JETIR1906638.pdf

"Modeled Sensor Database for IOT Aiming Efficient Data Storage", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp380-389, June-2019, Available at : http://www.jetir.org/papers/JETIR1906638.pdf