Browsing by Author "de Silva, R."

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • Thumbnail Image
    PublicationEmbargo
    Automated Water-Gate Controlling System for Paddy Fields
    (2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Sanjula, W.A.K.L.; Kavinda, K.T.W.; Malintha, M.A.K.; Wijesuriya, W.M.D.L.; Lokuliyana, S.; de Silva, R.
    The Internet of things (IoT) is an attractive technology being used in almost every aspect of the world today. It allows connecting any of the objects that want to communicate with each other and to transfer data without human interaction. In this paper proposed system is discussed on canal automation for a smart irrigation system using IoT concepts. Automated Water Gate Controlling System collects few environmental factors through a smart module embedded with sensors to communicate with the water gate of the paddy field. Cloud computing is used to store a large amount of data gathered by the sensor module. All real-time sensed data are processed and demonstrated on a web dashboard with a convenient graphical user interface along with a rain and reservoir water level prediction analysis to the users. Automation supports distance monitoring and controlling by allowing minimum human intervention. This paper provides a solution for traditional irrigation systems to confront rural farming interferences and global climatic changes via a cloudbased automated wireless communication system to water their paddy fields, monitor them and smartly control them.
  • Thumbnail Image
    PublicationEmbargo
    Smart Monitoring and Disease Detection for Robotic Harvesting of Tomatoes
    (2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Pasindu, I.; Viraj, S.; Dilshan, R.; Kalhara, A.; Senaweera, O.; de Silva, R.; Jayawardena, C.
    Tomato is a one of the most popular produced and extensively consumed vegetables in the world. Typical agricultural systems make extensive use of human labor which is more costly and less effective. This research explores the minimization of human labor through automation. The diseases infected by tomato plants are hard to detect. Identifying these diseases in advance would save the cultivation of the disease from spreading, thereby saving the crop.It is also a difficult task to recognize the ripe harvest and experienced labor is required. The efficiency of the harvesting method will be increased by automating the identification process of ripened fruits. Manually picking tomatoes can cause some harm to the fruits during plucking due to inconsistencies in human labor. Such damage will be reduced through a better implemented robotic scheme. This paper presents the development of autonomous system for tomato harvesting and disease detection.