ScienceDirect Available online at www.sciencedirect.com Procedia Computer Science 167 (2020) 1250–1257 1877-0509 © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientifc committee of the International Conference on Computational Intelligence and Data Science (ICCIDS 2019). 10.1016/j.procs.2020.03.440 © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientifc committee of the International Conference on Computational Intelligence and Data Science (ICCIDS 2019). Farming and agriculture accounts for a major portion of GDP (Gross Domestic Product) not only of developing countries but also for many developed nations. Thus, improvising and optimizing the current farming technologies is the need of the hour. It will not only help in flourishing sustainable development of mankind, flora and fauna but will also help in dealing with the global crisis such as climate change and epidemics such as draught. With better technology comes better yield; thus, will help prevent situations like starvation and malnutrition. The technology should be available at an affordable price so that its impact could reach to billions of people worldwide. The smart home systems are being extensively research and developed but this major area of Agriculture and specially Smart Agriculture tends to lag behind other domains and require quite a lot of R&D to achieve sustainable goals not only at industrial level but at the root level of this agriculture industry. Automation of conventional irrigation techniques can lead to many folds increase in crop yield. This paper proposes a state-of- the-art solution to the farm Irrigation using IoT (Internet of Things) and Machine Learning techniques, a wireless sensor network field needs to be established throughout the farm field or even in the household garden to monitor all the parts of the field, The proposed research presents the best possible solution to the farm needs, irrigation needs based on various open source databases available online and Machine learning algorithms(Classification and Regression). Irrigation needs varies with the crops and that too with the seasons. During various phases of 1. Introduction Keywords: IoT;WSN;Machine Learning;Algorithms;Technology,Agriculture. In the current age of high competition and risk in markets, technological advancements are a must for better growth and sustainability. The same applies to the agriculture industry. Every farmer has high stakes on the crops, their yield and quality. Rising water issues and need for proper methodologies for farm maintenance is a hot issue that needs to be tackled at utmost propriety. An automation of irrigation systems in farms is proposed in this research. The proposed solution is based on the Internet of Things (IoT), which would be a cheaper and more precise solution to the farm needs. A Monitoring system whose main purpose is to solve the over irrigation, soil erosion and crop-specific irrigation problem will be developed to ease and efficiently manage Irrigation problems. Since it is a well-known fact that the water is a scarce resource and over wastage of such an essential resource should be minimized. The proposed solution will be developed by establishing a distributed wireless sensor network (WSN), wherein each region of the farm would be covered by various sensor modules which will be transmitting data on a common server. Machine learning (ML) algorithms will support predictions for irrigation patterns based on crops and weather scenarios. So, a sustainable approach to irrigation is provided in this paper. Abstract 1,3,4,5,6, Department of Computer Science, The NorthCap University, Sector 23-A ,Gurugram, 122017,Haryana, India 2 Dept. of Informatics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India Anneketh Vij 1 , Singh Vijendra 2 , Abhishek Jain 3 , Shivam Bajaj 4 , Aashima Bassi 5 , Arushi Sharma 6 International Conference on Computational Intelligence and Data Science (ICCIDS 2019) IoT and Machine Learning Approaches for Automation of Farm Irrigation System