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  Internet-Sensor Information Mining Using Machine Learning Approach  
  Authors : Shreya P. Amilkanthwar; Poonam Railkar; P. N. Mahalle
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Sensor networks are composed of multiple tiny, low power, low cost sensor nodes which are capable to collect data from environment i.e. pressure, temperature , weather , thermal etc and collaborate to forward it to their centralized backend such as sink or base station for further processing .There are lots of sensors & clusters of sensor which are connected to internet for the purpose of sharing , Communicating data over internet. In addition to this there are various web logs, sensor logs where big data posted by various users. It requires an efficient mining strategy to manage such a big data generated by sensors, also sensor networks collects data from dynamic environment that change over time. Such a dynamic behavior need machine learning techniques to provide appropriate, selective & useful information to users. This paper presents literature review of machine learning techniques used for mining purpose & proposed a high level algorithm for the unstructured, unsupervised dataset generated by sensor networks.


Published In : IJCSN Journal Volume 4, Issue 6

Date of Publication : December 2015

Pages : 860- 866

Figures :07

Tables : 01

Publication Link : Internet-Sensor Information Mining Using Machine Learning Approach




Shreya P. Amilkanthwar : Department of Computer Engineering, Savitribai Phule Pune University, Pune, Maharashtra 411041, India

Poonam Railkar : Department of Computer Engineering, Savitribai Phule Pune University, Pune, Maharashtra 411041, India

P. N. Mahalle : Department of Computer Engineering, Savitribai Phule Pune University, Pune, Maharashtra 411041, India








Sensor Networks

Data Mining

Internet Sensor Information

Machine Learning

As our objective is to enable clusters of sensor to share data over internet, and to apply machine learning algorithm for data mining of such data formed by sensors . Here paper presents study of various data mining algorithms as well as machine learning approaches used in data mining. Along with this here studied lightweight supervised machine learning algorithm. As we go through various types’ machine learning data mining algorithms, it seems that the unsupervised machine learning approach is more efficient. Since Supervised machine learning algorithms have some limitations, So we are going to design an Un-supervised machine learning algorithm for mining of Internet Sensor information. Our future work is to build a proposed work &to implement it.










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