Determining the Precise Work Area of Agriculture Machinery Using Internet of Things and Artificial Intelligence
Precisely measuring the work area of agriculture farm machinery is important for performing the authentication of machinery usage, better allocation of resources, measuring the effect of machinery usage on the yield, usage billing and driver’s behaviour. The manual measurement, which is a common pra...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-05-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/10/3365 |
| _version_ | 1797568140535660544 |
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| author | Muhammad Waleed Tai-Won Um Tariq Kamal Aftab Khan Adil Iqbal |
| author_facet | Muhammad Waleed Tai-Won Um Tariq Kamal Aftab Khan Adil Iqbal |
| author_sort | Muhammad Waleed |
| collection | DOAJ |
| description | Precisely measuring the work area of agriculture farm machinery is important for performing the authentication of machinery usage, better allocation of resources, measuring the effect of machinery usage on the yield, usage billing and driver’s behaviour. The manual measurement, which is a common practice is an error-prone and time-consuming process. The irregular fields make it even more difficult to calculate the work area. An automatic solution that uses smart technology and algorithms to precisely calculate the work area is crucial for the advancement of agriculture. In this work, we have developed a smart system that utilizes the Internet of Things (IoT), Global Positioning System (GPS) and Artificial Intelligence (AI) that records the movement of agriculture machinery and use it to measure the precise work area of its usage. The system couples the nearest neighbourhood algorithms with Contact-based mechanisms to find the precise work area for different shaped fields and activities. The system was able to record the movement of machinery and calculate its work area, regardless of how many times the machinery runs through a particular field. Our evaluation shows that the system was able to precisely find the work boundaries and calculate the area with a maximum of 9% error for irregular shapes. |
| first_indexed | 2024-03-10T19:52:09Z |
| format | Article |
| id | doaj.art-0e83cd85c83347139ffc09458502f5cb |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T19:52:09Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-0e83cd85c83347139ffc09458502f5cb2023-11-20T00:15:17ZengMDPI AGApplied Sciences2076-34172020-05-011010336510.3390/app10103365Determining the Precise Work Area of Agriculture Machinery Using Internet of Things and Artificial IntelligenceMuhammad Waleed0Tai-Won Um1Tariq Kamal2Aftab Khan3Adil Iqbal4Department of Information and Communication Engineering, Chosun University, Gwangju 61452, KoreaDepartment of Cyber Security, College of Science and Technology, Duksung Women’s University, Seoul 01369, KoreaDepartment of Computer Systems Engineering, University of Engineering and Technology (UET), Peshawar 25120, PakistanDepartment of Computer Systems Engineering, University of Engineering and Technology (UET), Peshawar 25120, PakistanDepartment of Computer Systems Engineering, University of Engineering and Technology (UET), Peshawar 25120, PakistanPrecisely measuring the work area of agriculture farm machinery is important for performing the authentication of machinery usage, better allocation of resources, measuring the effect of machinery usage on the yield, usage billing and driver’s behaviour. The manual measurement, which is a common practice is an error-prone and time-consuming process. The irregular fields make it even more difficult to calculate the work area. An automatic solution that uses smart technology and algorithms to precisely calculate the work area is crucial for the advancement of agriculture. In this work, we have developed a smart system that utilizes the Internet of Things (IoT), Global Positioning System (GPS) and Artificial Intelligence (AI) that records the movement of agriculture machinery and use it to measure the precise work area of its usage. The system couples the nearest neighbourhood algorithms with Contact-based mechanisms to find the precise work area for different shaped fields and activities. The system was able to record the movement of machinery and calculate its work area, regardless of how many times the machinery runs through a particular field. Our evaluation shows that the system was able to precisely find the work boundaries and calculate the area with a maximum of 9% error for irregular shapes.https://www.mdpi.com/2076-3417/10/10/3365area estimationagriculture machineryartificial intelligenceGPS |
| spellingShingle | Muhammad Waleed Tai-Won Um Tariq Kamal Aftab Khan Adil Iqbal Determining the Precise Work Area of Agriculture Machinery Using Internet of Things and Artificial Intelligence Applied Sciences area estimation agriculture machinery artificial intelligence GPS |
| title | Determining the Precise Work Area of Agriculture Machinery Using Internet of Things and Artificial Intelligence |
| title_full | Determining the Precise Work Area of Agriculture Machinery Using Internet of Things and Artificial Intelligence |
| title_fullStr | Determining the Precise Work Area of Agriculture Machinery Using Internet of Things and Artificial Intelligence |
| title_full_unstemmed | Determining the Precise Work Area of Agriculture Machinery Using Internet of Things and Artificial Intelligence |
| title_short | Determining the Precise Work Area of Agriculture Machinery Using Internet of Things and Artificial Intelligence |
| title_sort | determining the precise work area of agriculture machinery using internet of things and artificial intelligence |
| topic | area estimation agriculture machinery artificial intelligence GPS |
| url | https://www.mdpi.com/2076-3417/10/10/3365 |
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