Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/474596
Title: | IoT for Health Ecosystem |
Researcher: | Modha, Hiren J |
Guide(s): | Kothari, Ashish M |
Keywords: | Agriculture Deep Learning Ecosystem Health Engineering Engineering and Technology Engineering Electrical and Electronic Machine Learning |
University: | Atmiya University |
Completed Date: | 2023 |
Abstract: | The primary goals of this research are to improve agricultural productivity and make the ecosystem newlinesparkle. The remote sensing-based approach is used to improve the quick feedback newlinesystem for decision support. Different Machine Learning and Deep Learning techniques can newlinebe used to provide subsequent executions enough time. Due to the fact that climate variables newlinevary from region to region on earth, care should be made to avoid generalising the established newlinemodel to the entire globe. In order for everyone to use the system, the cost is also considered. newlineWith various prediction approaches, it should be possible to monitor various agricultural newlinediseases at an early stage and treat them as needed to save the crop. The many phases of crop newlinedevelopment have been recognised, and it should be possible to inject more neutrinos during newlinespecific times to boost production. In order to avoid crops from being destroyed by a lack of newlinemoisture in the farm, the damaging effects of drought will be eliminated by ongoing soil newlinemoisture monitoring. Additionally, it is feasible to conserve water and improve the health of newlinethe environment. newline |
Pagination: | 180 |
URI: | http://hdl.handle.net/10603/474596 |
Appears in Departments: | Electronics & Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title page.pdf | Attached File | 429.75 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 2.53 MB | Adobe PDF | View/Open | |
03_contents.pdf | 450.34 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 382.67 kB | Adobe PDF | View/Open | |
05_ch-1.pdf | 521.45 kB | Adobe PDF | View/Open | |
06_ch-2.pdf | 745.21 kB | Adobe PDF | View/Open | |
07_ch-3.pdf | 1.43 MB | Adobe PDF | View/Open | |
08_ch-4.pdf | 2.05 MB | Adobe PDF | View/Open | |
09_ch-5.pdf | 2.11 MB | Adobe PDF | View/Open | |
10_annexures.pdf | 1.6 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 897.51 kB | Adobe PDF | View/Open |
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