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Sustainable Farming in Soilless Culture Non-Circulating Kratky Method Using Fuzzy Logic Control and Measure Greenness
(2022-01) WANNIACHCHI, L. R; JAYAKODY, A
Organic horticulture and organic commodities have to face severe rivalry in today's economic environment. Even though there are several forms of home gardening, there is a need for a more organized and structured need has arisen. In horticultural, plants are planted on the water as a substitute for soil, it is feasible to achieve great efficiency although might be more suitable. Feeding the seedlings with the appropriate nutrients and hormones, as well as oxygen, is critical to the plant's vitality. The plant requires these chemicals and supplying them to the roots of plants would guarantee that the plant obtains the nutrients and oxygen it requires on a constant schedule. The system's strength is to give the plant the necessary oxygenation through the Air Roots of the seedlings being planted. The plant needs oxygen as well as nutrients from these root fibers as it grows over time, the amount of fiber required to extract oxygen will rise. The intensity of chlorophyll on the leaves can be determined by evaluating the quality of the plant and its nature. A more robust process is required considering urban expansion and human involvement is limited. To overcome these situations systems used to employ the latest IoT and microcontroller technologies. This study to control ecosystems introduce fuzzy logic controls and use a computer vision-based approach to computing plant greenness.
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Automated Attendance Monitoring System Using IoT
(2019 1st International Conference on Advancements in Computing (ICAC), SLIIT, 2019-12-05) Kovelan, P.; Thisenthira, N.; Kartheeswaran, T.
Most of the process is automated to reduce human intervention and manual mistakes in this busy world. It will be easy if we can automate some complex, sensitive activities of day to day life. This paper discusses a smart attendance system that automatically monitors and manages the attendance of students in an educational institution. Further, this system makes automated analysis and prepares a detailed report weekly, monthly and annually. The whole system is developed with an Arduino microcontroller and RFID readers. Also, GSM and Wi-Fi communication modules are used to make convenient communication depend on the availability of the network. A microchip (microSD) is placed to store data in case of communication failure and those stored data will be uploaded bulk when the communication channel is restored. This system will reduce a lot of manual work of educators and education administrators of an education institution
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E-Agrigo
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Kartheepan, T.; SirigajanK, B.; Subangan, K.; Mohammed Azzam, M.A.; Bandara, P.; Mahaadikara, M.M.D.J.T.H.
To feed this population, food production should be increased by at least 70%. Developing nations have a vast potential to increase the amount of food produced by doubling the current production. However, the traditional methods of farming are making agriculture unviable and inefficient. The increasing food production needs to be met by double the current level of farming. The conventional of farming is making industry uncompetitive and inefficient. This paper aims to analyze the various factors that affect the implementation of autonomous machinery in agriculture. The development of autonomous machinery for agriculture has emerged as vital step towards achieving this goal. Now a day’s farmers are planning their cultivation by finding proper weather and geographical condition on their own experience, but they are failing to cultivate profitable crop and unaware of the diseases that will affect their crops, sometimes these diseases may affect their whole crops and let the farmers to sink in zero profit. Despite these issues plays a major role, there are some other problems also have an impact like, lack of irrigation plans and question of how and where to sell their cultivated crops. By considering these major threats we have planned to propose a solution to some of the selected issues. This can be achieved by applying machine learning algorithm, Image processing and IOT systems. By using our platform farmers will get a chance to plan their yield in a profitable way by using our optimized weather and geographical data.

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