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Chetan Bhatt

Bio: Chetan Bhatt is an academic researcher from Government Engineering College, Sreekrishnapuram. The author has contributed to research in topics: Decision support system & Smart grid. The author has an hindex of 5, co-authored 12 publications receiving 59 citations. Previous affiliations of Chetan Bhatt include Indian Institute of Science & Centre For Electronics Design And Technology.

Papers
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Journal ArticleDOI
01 Mar 2015
TL;DR: Fuzzy logic based calibration of the constants CH and EH in the Hargreaves equation for diverse climate locations of India like Bikaner, Calcutta, Kakinada, Coimbatore, Panjim-Goa, Kota, Deharadun, and Srinagar is performed and validated as mentioned in this paper.
Abstract: Standard model for estimation of reference evapotranspiration rate (ET0) is the FAO-56 version of Penman–Monteith. It needs a wide range of atmospheric parameters like solar radiations, wind speed, air temperature, humidity, vapor pressure and soil heat flux. All these data may not be available at the majority of the locations. The estimation of evapotranspiration using the Hargreaves equation is a potential solution to this problem. It needs only temperature and radiation data to estimate ET0. But, simplification brings inaccuracy and need for regional calibration of the Hargreaves equation constants—CH and EH. Fuzzy logic based calibration of the constants CH and EH in the Hargreaves equation for diverse climate locations of India like—Bikaner, Calcutta, Kakinada, Coimbatore, Panjim-Goa, Kota, Deharadun, and Srinagar is performed and validated. Performance of modified Hargreaves equation (MHG) is compared with Hargreaves equation (HG) and FAO-56 version of Penman–Monteith (PM-56). MHG resulted in improvement by reducing the error in ET0 estimates. The root mean square error (RMSE) values reduce with the range 0.36–0.92 mm/day for MHG from 1.12 to 2.53 mm/day of HG. Location specific calibration improves the accuracy of the HG.

15 citations

Proceedings ArticleDOI
01 Nov 2013
TL;DR: F fuzzy logic based structure for the plant disease forecasting system is proposed and it has been demonstrated that the proposed method can be implemented with minimum weather data like-temperature and humidity.
Abstract: Integrated Pest Management (IPM) is a comprehensive approach that integrates a variety of practices to minimize the loss of farm productions due to pests and pathogens with optimum use of pesticides Early detection of pest and its control is one of the aspects of IPM Weather based forecasting is well accepted method for this Various meteorological data like-temperature, humidity, leaf wetness duration (LWD) plays the vital roles in the growth of microorganism responsible for disease Effective forecasting of such diseases on the basis of climate data can help the farmers to take timely actions to restrain the diseases This can also rationalize the use of pesticides, which are one of the causes behind land pollution Weather based forecasting system can be considered as a part of the Agricultural Decision Support System (ADSS) which is Knowledge Based System (KBS) This paper proposes fuzzy logic based structure for the plant disease forecasting system It has been demonstrated that the proposed method can be implemented with minimum weather data like-temperature and humidity

14 citations

Journal ArticleDOI
TL;DR: Patel et al. as mentioned in this paper proposed a fuzzy logic based calibration method for the Hargreaves equation and validated the performance of the method at eight geographically different locations of India with diverse climate conditions.
Abstract: Patel J., Patel H., Bhatt C . (2014): Generalized calibration of the Hargreaves equation for evapotranspiration under different climate conditions . Soil & Water Res., 9: 83–89. Accurate estimation of evapotranspiration (ETo) is a key factor in weather-based irrigation scheduling methods. To estimate ETo using the Hargreaves equation, just the data on the minimum and maximum temperature and solar radiation are required. However, this procedure cannot offer consistent accuracy for different climate conditions. To attain the accuracy, calibration of the equation constants ( C H and E H ) for different climate condi tions have successfully been attempted by many researchers. Because these calibration procedures are lengthy and location-specific, there is a need of a generalized calibration method to make the Hargreaves equation more pertinent and effective. In this paper, fuzzy logic based calibration method for the Hargreaves equation is proposed and validated. The fuzzy inference system is developed to compute appropriate values of the con stants C H and E H on the basis of past data on humidity and wind velocity of a selected location. The underlying relationship between weather conditions and the best values of the constants C H and E H are used to establish a fuzzy rule base. The performance of the method is checked at eight geographically different locations of India with diverse climate conditions. The Mean Absolute Error (MAE) in ETo values estimated by the calibrated modified Hargreaves equation and the Penman-Monteith (PM) equation is in the range of 0.3220–1.0325. It is far more lower than if the error is calculated using the original Hargreaves equation. It confirms the correctness of the calibration method for different climate conditions.

12 citations

Proceedings ArticleDOI
01 Dec 2011
TL;DR: WSN based expert system is proposed to provide optimized water supply for various crops in the field using on field soil moisture and temperature data to understand the actual need of water.
Abstract: Increased demand of farm product due to population growth and limited resources of irrigation water has made the field irrigation management system as an important element of agricultural activity. Wireless Sensor Network (WSN) is the most preferred platform due to its low cost, small size, low power consumption, reduced maintenance, great flexibility, portability and scalability features. WSN based expert system is proposed to provide optimized water supply for various crops in the field. It uses on field soil moisture and temperature data to understand the actual need of water.

12 citations

Book ChapterDOI
01 Jan 2020
TL;DR: In this article, the authors have proposed guidelines and recommendations for smart building automation for smart cities with interesting discussions of example case studies and implemented proof-of-concept concepts, where the authors keep their major emphasis on automatic monitoring of critical parameters.
Abstract: Globally, many smart cities have been observed developing in different countries to offer high quality life and excellent working-living environment to their citizens. Being powerhouses of potential and skilled workers, smart cities contribute immensely to the overall development of the society and nation. As Smart home or smart building contributes at the core of effective smart city realization as an important and basic building block, for long term sustainable growth, it becomes quite imperative to monitor critical environmental parameters of building to make the life quite liveable. Such smart buildings monitored by Building Automation Systems (BAS), which have started demonstrating rapid growth potential on account of rising energy costs, stringent scarcity of fossil fuels for power stations and continuous abnormal-unpredictable climate changes, etc. Smart buildings with energy efficiency are need of the day and frequent terrorist attacks and rising security concerns worldwide, security and surveillance have been major focused areas today, where BAS are providing solutions. This chapter keeps its major emphasis not only on automatic monitoring of critical parameters, but also suggest technological approaches. Optimized utilization of energy usage, integration of renewables as well as with smart grid (energy backbone of smart city) shall also be covered in broad perspectives. The chapter shall suggest useful guidelines and recommendations for smart building automation for smart cities with interesting discussions of example case studies and implemented proof of concepts.

10 citations


Cited by
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Journal ArticleDOI
01 Jun 2019
TL;DR: In this article, a survey of the work of many researchers to get a brief overview about the current implementation of automation in agriculture is presented and a proposed system which can be implemented in botanical farm for flower and leaf identification and watering using IOT.
Abstract: Agriculture automation is the main concern and emerging subject for every country. The world population is increasing at a very fast rate and with increase in population the need for food increases briskly. Traditional methods used by farmers aren't sufficient enough to serve the increasing demand and so they have to hamper the soil by using harmful pesticides in an intensified manner. This affects the agricultural practice a lot and in the end the land remains barren with no fertility. This paper talks about different automation practices like IOT, Wireless Communications, Machine learning and Artificial Intelligence, Deep learning. There are some areas which are causing the problems to agriculture field like crop diseases, lack of storage management, pesticide control, weed management, lack of irrigation and water management and all this problems can be solved by above mentioned different techniques. Today, there is an urgent need to decipher the issues like use of harmful pesticides, controlled irrigation, control on pollution and effects of environment in agricultural practice. Automation of farming practices has proved to increase the gain from the soil and also has strengthened the soil fertility. This paper surveys the work of many researchers to get a brief overview about the current implementation of automation in agriculture. The paper also discusses a proposed system which can be implemented in botanical farm for flower and leaf identification and watering using IOT.

428 citations

Journal ArticleDOI
TL;DR: In this article, a spatial and temporal study of the potential evapotranspiration (ETo) in arid, semi-arid, Mediterranean, and very humid regions is presented.

236 citations

Journal ArticleDOI
TL;DR: This survey focuses on providing a comprehensive review of the techniques and strategies for making cities smarter, sustainable, and eco-friendly and on IoT and its capabilities to merge into aspects of potential to address the needs of smart cities.
Abstract: The development of the Internet of Things (IoT) technology and their integration in smart cities have changed the way we work and live, and enriched our society. However, IoT technologies present several challenges such as increases in energy consumption, and produces toxic pollution as well as E-waste in smart cities. Smart city applications must be environmentally-friendly, hence require a move towards green IoT. Green IoT leads to an eco-friendly environment, which is more sustainable for smart cities. Therefore, it is essential to address the techniques and strategies for reducing pollution hazards, traffic waste, resource usage, energy consumption, providing public safety, life quality, and sustaining the environment and cost management. This survey focuses on providing a comprehensive review of the techniques and strategies for making cities smarter, sustainable, and eco-friendly. Furthermore, the survey focuses on IoT and its capabilities to merge into aspects of potential to address the needs of smart cities. Finally, we discuss challenges and opportunities for future research in smart city applications.

71 citations

Journal ArticleDOI
TL;DR: In this article, a deep neural network (DNN) was employed for incorporating historical data and predicting future crop evapotranspiration (ETc) values to eliminate the limitations mentioned, and analyze the long-term dynamics of ETc based on limited climate data and simple method.

60 citations

Journal ArticleDOI
TL;DR: The findings showed that determination-coefficient between historical-predicted crop evapotranspiration (ETc) varied from 0.92 to 0.97 for two crops, which will help in optimal planning of future water under climate change in the agricultural sector.

57 citations