Application of Supervised Machine Learning Algorithm with an Intrusion Detection System for Grazing Animals’ Detection

Abstract

Over the years, computer technology has contributed in the area of innovation
and creativities through ideas put together in the areas of programming, machine
learning, artificial intelligence, data science, and big data analytics, to unveil
hidden pattern and make meaningful insight to data analysis result for better
decision making. Considering the peculiarities and device techniques for
farming, there is a need for more technological approaches to be inculcated into
farming. Farmers today are faced with the challenge posed by grazing animals
which has been the major issue surrounding farmers, this occurred in an
environment like Nigeria where open grazing is allowed. In this paper, we
developed an algorithm for grazing animals’, detection system using a supervised
machine learning algorithm with an intrusion detection system and classification
model. The algorithm uses the signature-based intrusion technique to report a
situation that matches a pattern corresponding to a known attack type. The
result of the trained dataset and model classification was able to detect grazing
animals (cows) with non-grazing animals (dogs). And we got (1.000 =100%)
accuracy level of the trained and fitted model.