Environment is the key factor in the greenhouse system. To provide monitoring and controlling facility inside the greenhouse, IoT based system is more flexible and suitable solution. To maintain the proper environment inside the green- house, we have designed the system with heating, cooling and water supply facility by integrating the system with heater, cooling fan and water pump. The temperature, humidity and the soil moisture inside the greenhouse continuously monitored and controlled over online platform.
The motive of the investigation is analyzing the categorization of fetal state code from the Cardiographic data set based on decision tree method. Cardiotocography is one of the important tools for monitoring heart rate, and this technique is widely used worldwide. Cardiotocography is applied for diagnosing pregnancy and checking fetal heart rate state condition until before delivery. This classification is necessary to predict fetal heart rate situation which is belonging. In this paper, we are using three input attributes of training data set quoted by LB, AC, and FM to categorize as normal, suspect or pathological where NSPF variable is used as a response variable. After drawing necessary analysis into three variables we get the 19 nodes of classification tree and also we have measured every single node according to statistic, criterion, weights, and values. The Cardiotocography Dataset applied in this study is received from UCI Machine Learning Repository. The dataset contains 2126 observation instances with 22 attributes. In this experiment, the highest accuracy is 98.7%. Overall, the experimental results proved the viability of Classification and Regression Trees and its potential for further predictions.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.
Wireless Sensor nodes are small, low power consumption nodes which are basically used for sensing, transmitting and receiving the target values to specify nodes. Basically, we deploy nodes to collect information about specific region and to know about current and future results. Wireless Sensor Networks have various applications in many fields e -g disaster management, biological detection, and traffic, pollution, civil infrastructure monitoring and S urveillance. In this paper, our main purpose is to examines the deployment methodology for a WS N.. This paper also provide general overview and importance on multi-objective strategies, their assumptions, and optimization. In this paper we studies and surveys different sensor deployment methodologies with their ad vantages and disadvantages.
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