Heuristics of Machine Learning for Home Intrusion Detection Application

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Abstract

Security has become a very vital role in present modern world. We need security for various applications and for our data. In particular security in home application is very crucial. So to serve this purpose in an efficient and easy manner we developed an intrusion system where in HOG (Histogram of Oriented Gradients) algorithm is used to detect person and an API to give alerts for intrusion. HOG is the Machine Learning (ML) algorithm used particularly for the person detection. The API used here is TWILIO which is the most suitable API for sending messages within seconds and accurately. Since every system is becoming automated we focused more on implementing the HOG and making the system to learn by itself and perform accurate results. In this paper we explained how HOG algorithm is implemented to detect the person entering the house and send the alerts as the person is detected. The accuracy of the model along with further developments that can be possible is given in detail.

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Sneha*, C. N., Sreenidhi, I., & Satyanarayana, P. (2019). Heuristics of Machine Learning for Home Intrusion Detection Application. International Journal of Innovative Technology and Exploring Engineering, 9(2), 2298–2301. https://doi.org/10.35940/ijitee.b7408.129219

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