IoT data analytics for operational status tracking in the agriculture field
The research and development of a sustainable, effective, and productive plant growth monitoring system is a key factor that is concerned by the whole agriculture industry. The demand for getting more enhanced systems is a continuous activity in the whole development process and is different based o...
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| Format: | Final Year Project / Dissertation / Thesis |
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2023
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| Online Access: | http://eprints.utar.edu.my/5774/ http://eprints.utar.edu.my/5774/1/fyp_CS_2023_YYH.pdf |
| _version_ | 1848886501220286464 |
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| author | Yong, Yu Hong |
| author_facet | Yong, Yu Hong |
| author_sort | Yong, Yu Hong |
| building | UTAR Institutional Repository |
| collection | Online Access |
| description | The research and development of a sustainable, effective, and productive plant growth monitoring system is a key factor that is concerned by the whole agriculture industry. The demand for getting more enhanced systems is a continuous activity in the whole development process and is different based on the different types of planting methods. As in hydroponics, it has several parameters that would decide whether the planting process would provide a better harvest compared to others such as water level, light, water nutrient, etc. And with a successful arrangement of these parameters, there are also several ways to measure the growth rate of a plant like weight, height, and leaf colour. So, the problem is how to build a system that can capture and record any abnormal situation that happened in order to get a great monitoring system. Many monitoring systems already occur in the market or proposed in a paper, but nothing is perfect, there are also contain some issues in these existing systems like the cost, the accuracy, or even the universality and the biggest issue is the market is still lack of datasets for the research and statistic used in this field. To solve these problems and limitations, this present system would propose a plant growth monitoring system that applies the Raspberry Pi camera to provide a plant growth dataset that is uncommon and difficult to find in the market. After fulfilling and completing the development of the whole system, it can be expected to provide a monitoring system that can monitor the daily operation of the system and also import the growth rate data to create a demanded dataset. |
| first_indexed | 2025-11-15T19:39:30Z |
| format | Final Year Project / Dissertation / Thesis |
| id | utar-5774 |
| institution | Universiti Tunku Abdul Rahman |
| institution_category | Local University |
| last_indexed | 2025-11-15T19:39:30Z |
| publishDate | 2023 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utar-57742023-09-08T14:04:49Z IoT data analytics for operational status tracking in the agriculture field Yong, Yu Hong Q Science (General) T Technology (General) The research and development of a sustainable, effective, and productive plant growth monitoring system is a key factor that is concerned by the whole agriculture industry. The demand for getting more enhanced systems is a continuous activity in the whole development process and is different based on the different types of planting methods. As in hydroponics, it has several parameters that would decide whether the planting process would provide a better harvest compared to others such as water level, light, water nutrient, etc. And with a successful arrangement of these parameters, there are also several ways to measure the growth rate of a plant like weight, height, and leaf colour. So, the problem is how to build a system that can capture and record any abnormal situation that happened in order to get a great monitoring system. Many monitoring systems already occur in the market or proposed in a paper, but nothing is perfect, there are also contain some issues in these existing systems like the cost, the accuracy, or even the universality and the biggest issue is the market is still lack of datasets for the research and statistic used in this field. To solve these problems and limitations, this present system would propose a plant growth monitoring system that applies the Raspberry Pi camera to provide a plant growth dataset that is uncommon and difficult to find in the market. After fulfilling and completing the development of the whole system, it can be expected to provide a monitoring system that can monitor the daily operation of the system and also import the growth rate data to create a demanded dataset. 2023-01 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/5774/1/fyp_CS_2023_YYH.pdf Yong, Yu Hong (2023) IoT data analytics for operational status tracking in the agriculture field. Final Year Project, UTAR. http://eprints.utar.edu.my/5774/ |
| spellingShingle | Q Science (General) T Technology (General) Yong, Yu Hong IoT data analytics for operational status tracking in the agriculture field |
| title | IoT data analytics for operational status tracking in the agriculture field |
| title_full | IoT data analytics for operational status tracking in the agriculture field |
| title_fullStr | IoT data analytics for operational status tracking in the agriculture field |
| title_full_unstemmed | IoT data analytics for operational status tracking in the agriculture field |
| title_short | IoT data analytics for operational status tracking in the agriculture field |
| title_sort | iot data analytics for operational status tracking in the agriculture field |
| topic | Q Science (General) T Technology (General) |
| url | http://eprints.utar.edu.my/5774/ http://eprints.utar.edu.my/5774/1/fyp_CS_2023_YYH.pdf |