International Journal of Computer Science and Engineering

11-26

Authors: Muktevi Srivenkatesh

Chronic kidney disease is rising health hassles and includes stipulations that minimize the efficiency of renal features and that damage kidneys. Chronic kidney sickness may be detected with countless machine learning techniques, and these have been classier. The use of a number features and classier combinations. Methods: In this study, we applied 12 one of a kind of machine learning classifiers (Naïve Bayes, RandomTree, REPTree, etc.) for the analysis of Chronic kidney disease. The classification performances are evaluated with five different overall performance metrics, i.e., accuracy, kappa, Mean absolute error (MAE), Root Mean square error (RMSE) and Fmeasures. The goal of this lookup work is to predict kidney disease with the aid of using more than one computing machine learning algorithms that are J48 Graft Decision tree (C4.5) and Bayesian Network (BN) and LMT, LAD Tree, Random Tree and Random Forest, etc. Results: The machine learning algorithms under study were able to predict liver disease in patients with accuracy between 76.13% and 83.41%. Conclusions: It was shown that Random forest has better Accuracy (83.41%) when compared to different machinelearning algorithms.

43-48

Authors: Shreedatta Sawant, Ashwina Tari Volvoikar, Kiran Mukund Gawas, Deodato Idris Marcel Rodrigues, Shrutika Sharad Pedamkar, Prasad Balkrishna Salgaonkar & Rohit Arvind Narvekar

Due to the rapid production of number of vehicles, traffic problems are bound to exist. The number of vehicles has been increasing on a daily basis, which adds to the parking constraints at public places. The proposed system, “Smart Parking System” is designed to alleviate the current problems. With the implementation of the smart parking system, user can easily locate and reserve a vacant parking space at any car parking area which is convenient to them. Checking in and checking out of vehicles is also made easier and more convenient to the drivers with the help of Node MCU (ESP8266) and Ultrasonic sensor. In today’s world, smart cities have become very popular. The evolution of Internet of Things has made it possible to achieve smart parking system. Problems such as, traffic congestion, limited car parking facilities and road safety are being addressed by IoT. In case the parking is not available in the desired location, the proposed system also allows the user to search for nearby available parking area. Using Naïve Bayes Classifier algorithm the user can also search for the availability status of a parking area for any particular day. Due to the rapid production of number of vehicles, traffic problems are bound to exist. The number of vehicles has been increasing on a daily basis, which adds to the parking constraints at public places. The proposed system, “Smart Parking System” is designed to alleviate the current problems. With the implementation of the smart parking system, user can easily locate and reserve a vacant parking space at any car parking area which is convenient to them. Checking in and checking out of vehicles is also made easier and more convenient to the drivers with the help of Node MCU (ESP8266) and Ultrasonic sensor. In today’s world, smart cities have become very popular. The evolution of Internet of Things has made it possible to achieve smart parking system. Problems such as, traffic congestion, limited car parking facilities and road safety are being addressed by IoT. In case the parking is not available in the desired location, the proposed system also allows the user to search for nearby available parking area. Using Naïve Bayes Classifier algorithm the user can also search for the availability status of a parking area for any particular day.