Gautam Kumar
Gautam Kumar currently works at the Department of Computer Application, Maharishi Markandeshwar (Deemed to be) University, Mullana, Ambala. Gautam does research in Information Science, Programming Languages and Computer Communications (Networks). Their most recent publication is "POLLUTION MANAGEMENT THROUGH INTERNET OF THINGS: A SUBSTANTIAL SOLUTION FOR SOCIETY".
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cut its further spread. Looking at the COVID-19 trend in India, the first case was reported in late January 2020, since then, number of positive cases is increasing continuously. To tackle the situation, Hon’ble Prime Minister of India, Mr. Narendra Modi, called for Janta Curfew of one day and thereafter declared a 21 days lockdown till April 14th, 2020 to break the chain of coronavirus transmission. The India has more than 1552 COVID-19 cases with 49 deaths, and 102 completely recovered cases by 31st March, 2020.
Methodology: The methodology behind this study is to identify trends and review the open challenges, application areas and architectures for IoT in agro-industry. This survey is based on a systematic literature review where related research is grouped into four domains such as monitoring, control, prediction, and logistics.
Main Findings: This research study presents a detailed work of the eminent researchers and designs of computer architecture that can be applied in agriculture for smart farming. This research study also highlights various unfolded challenges of IoT in agriculture.
Implications: This study can be beneficial for farmers, researchers, and professionals working in agricultural institutions for smart farming.
Novelty/Originality of the study: Various eminent researchers have been making efforts for smart farming by using IoT concepts in agriculture. But, a bouquet of unfolded challenges is still in a queue for their effective solution. This study makes some efforts to discuss past research and open challenges in IoT based agriculture.
SCA with local search is comparable to memetic algorithms.
Keywords: Fuzzy Systems, Genetic Algorithms (GAs), Memetic Algorithms (MAs), Particle Swarm Optimization (PSO), Sine Cosine Algorithms (SCA).
Methodology: The proposed framework is an IOT unit for handling these issues, including powerful use of the different sensor, to capture the estimations of various sorts of toxins in the earth and show insights on a site which can be gotten to by all clients for nothing. The research data is collected from the different sensors installed at different locations in our surroundings. After collecting data from sensors, a comparative study of data is carried out with the standards provided by the Central Pollution Control Board (CPCB).
Results: The proposed system helps to reduce the pollution in our environment and as a result of which pollution can be reduced by taking major steps towards it.
Application/Implications: The framework we are proposing is a propelled answer for observing the ecological contamination at a specific spot and make data available for each person.
Novelty/originality of the study: Our proposed system ensures that pollution which ultimately causes health, environmental and other social problems can be tracked from time to time and each and every person in the society can track and check pollution level in their surroundings.