• Login
    View Item 
    •   NM-AIST Home
    • Computational and Communication Science Engineering
    • Masters Theses and Dissertations [CoCSE]
    • View Item
    •   NM-AIST Home
    • Computational and Communication Science Engineering
    • Masters Theses and Dissertations [CoCSE]
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Development of an IoT-based smart irrigation system for efficient water management in Uasin Gishu County

    Thumbnail
    View/Open
    Full text (3.475Mb)
    Date
    2024-08
    Author
    Bundotich, Winny
    Metadata
    Show full item record
    Abstract
    Agriculture is the backbone of Kenya’s economy, with Uasin Gishu county being the country’s breadbasket. Food scarcity has recently increased due to climate change, population growth, and decreased land available for farming. Several measures have been implemented to mitigate food scarcity, including encouraging irrigation farming to ensure whole-year food production. However, irrigation practice faces a water scarcity challenge. Efforts have been put in place to improve water use efficiency. These measures include scheduled irrigation system technology. Most of these scheduled systems target greenhouse irrigation and leave out open-field irrigation farmers where rainfall is a factor in reducing water wastage whenever there is rainfall. This technology does not provide a precision of plant water needs and poses a risk of under or over irrigation. Therefore, to overcome these challenges, this project developed an IoT-based system with sensors to monitor critical soil parameter measurements continuously. The main objective of this project was to develop an IoT-based smart irrigation system for efficient water management. An ESP32 microcontroller board is used to process information collected from the sensors. Openweather API is implemented on the Thingsboard cloud platform to fetch rainfall prediction information. While providing remote valve control, the system uses soil moisture level and rainfall prediction parameters to automatically control the irrigation valves. The system also offers rich farm information visualization through the Thingsboard cloud platform dashboard, which can be accessed remotely through the Thingsboard live mobile application, where a user can control the irrigation valves remotely. Mixed methods which involved questionnaires and focus group discussions was used to collect data from sixteen respondents. Purposve sampling was also used to identify the respondents during data collection. To develop the system,agile software development methodology, specifically extreme programming (XP) was implemented. To validate the system’s functionalities, the system was demonstrated to twenty seven people and thereafter were allowed to interact with the system. A questionnaire was implemented to get feedback from the respondents. Generally, respondents agreed that the system satisfactorily met their needs. The developed system contributes to the value chain by providing precise water input. The system can be advanced to include other essential features needed to monitor and evaluate irrigated farms within Uasin Gishu county and any other region.
    URI
    http://doi.org/10.58694/20.500.12479/2948
    Collections
    • Masters Theses and Dissertations [CoCSE]

    Nelson Mandela-AIST copyright © 2021  DuraSpace
    Theme by 
    Atmire NV
     

     

    Browse

    All PublicationsCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Nelson Mandela-AIST copyright © 2021  DuraSpace
    Theme by 
    Atmire NV