Multi agent based extension support system for horticulture
Most of the medium- and small-scale horticultural farmers rely on public extension service providers while large-scale farmers depend on private extension services. However, the current number of extension service providers is inadequate to meet the needs of horticultural farmers. HCDA offers limited specialized extension services for export crops and only in specific highconcentration areas. Consequently, high-potential regions and farmers who produce for the local market have not benefited from this service. The purpose of this project is to address the extension service problem by identifying extension services information required in horticulture, to design and build the Multi agent based extension support system then test and evaluate the build multi agent based extension support system with farmers The information needs and searches for the farmer are related to 6 stages which were identified as follows: (1) Deciding, (2) Seeding, (3) Planting, (4) Diseases, (5) Harvesting, packing and storing, and (6) Marketing. The stages were the bases for building the multi agent based extension support system for horticulture. The system uses multi agents to perform search on behalf of the farmers and gives results on the mobile phone. An agent oriented methodology –Prometheus- was used in the analysis and design of the multiagent based extension support system for horticulture. The implementation of the multi agents was carried out using JADE and JADE-LEAP agent development kit. This framework opens the way towards any kind of distributed multi agent systems, in which farmer agents may be smoothly running on mobile devices and can communicate wirelessly with agents to access information on extension services. Test cases were run for the purpose of evaluating the built prototype with farmers. On average 91% of the farmers rated the functionality of the system excellent while on average 77% of the farmers rated the overall system excellent in terms of easy to use. The evaluation results also revealed that 87% of the farmers were motivated to use the program repeatedly while 75% of the farmers indicated that they would recommend this program to other farmers. Future improvements proposed are inclusion of GIS, data mining and language functionalities.