Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Automated Ground Harvesting Machine Using Image Processing

Author : Manjula S D 1 Chaitra C V A 2 Megha M 3 Rudragouda B 4 S Vinutha 5

Date of Publication :21st July 2021

Abstract: Agriculture is a main part of India's economy and at present it is among the top two rank makers in the world. This field provides roughly around 52 % of the total number of occupations in India and contributes around 18.1 percent to the GDP (Gross Domestic Product).For a country like India to gain profit it is necessary that rural and mechanical advancement ought to takeplace head to head.In India, the greater part of land used for rural section which produces semi-completed item. Around 65% of individuals rely upon agribusiness as a principle occupation.Since antiquated occasions cultivating is done physically which causes lesser efficiency and additional time requirement.The opportunity has arrived to modernize our cultivating cycle so profitability can be expanded. The fundamental target of the task is to build up the under grounded plants harvester thinking about the necessities of Indian ranchers. Among the field activities conserned with cultivation, collecting is the most difficult and exorbitant undertaking. Existing ground collectors are too gigantic to possibly be helpful for limited scope ranchers and in situation like multicroping. At first overview of common place ranch field has been done trailed by writing study, static examination, manufacture testing and plan adjustments. The existing harvester accessible currently is financially heavy which just only plucks the evacuated plants not the under established plants.

Reference :

    1. P. Udomkun, M. Nagle, D. Argyropoulos, B. Mahayothee, and J. Müller,''Multi-sensor way to deal with improve optical observing of papaya contract age during drying,'' J. Food Eng., vol. 189, pp. 82–89, Nov. 2016.
    2. Z. Wang, K. B. Walsh, and B. Verma, ''On-tree mango natural product size estima-tion utilizing RGB-D pictures,'' Sensors, vol. 17, no. 12, p. 2738, 2017.
    3. A. Tzounis, N. Katsoulas, T. Bartzanas, and C. Kittas, ''Internet of Things in agribusiness, ongoing advances and future difficulties,'' Biosyst. Eng., vol. 164, pp. 31–48, Dec. 2017.
    4. N. Torbick, D. Chowdhury, W. Salas vol. 9, no. 2, p. 119, 2017. .
    5. M Kulbacki, J Segen, W Kniec., "Overview OF DRONES FOR AGRICULTURE AUTOMATION FROM PLANTING" , 2018 IEEE 22ndieeexplore.ieee.org
    6. T.U. Rehman, M.S. Mahmud, Y.K. Chang, et al."Current and future utilizations of measurable AI calculations for rural machine vision systemsComput Electron Agric", 156 (2019), pp. 585-605
    7. A. Khanna and S. Kaur, ''Evolution of Internet of Things (IoT) and its huge effect in the field of exactness farming,'' Comput. Electron. Agricult., vol. 157, pp. 218– 231, Feb. 2019.
    8. Global Smart Farming Market to Reach $23.14 Billion by 2022.Accessed: Apr. 25, 2019. [Online]. Accessible: https://www.globenewswire.com/newsdischarge/2018/08/02/1546021/0/en/Global-SmartFarming-Market-to-Reach-23-14-Billion-by-2022.html
    9. Why IoT, Big Data and Smart Farming are the Future of Agri-culture. Gotten to: Apr. 17, 2019. [Online]. Accessible: https://www.businessinsider.com/web ofthings-shrewd horticulture 2016-10
    10. Huawei. The Connected Farm—A Smart Agriculture Market Assessment. Gotten to: Sep. 9, 2019. [Online]. Accessible: https://huaweihub. com.au/the-associated ranch a-keen horticulture market-evaluation/

Recent Article