D. Piplani, Dineshkumar Singh, K. Srinivasan, N. Ramesh, Anil Kumar, V. Kumar
{"title":"Digital Platform for Data Driven Aquaculture Farm Management","authors":"D. Piplani, Dineshkumar Singh, K. Srinivasan, N. Ramesh, Anil Kumar, V. Kumar","doi":"10.1145/2835966.2836277","DOIUrl":null,"url":null,"abstract":"Besides meeting the domestic needs of cheap animal protein, Indian fisheries, is source of livelihood for 14.5 million fishers [1]. During FY2014-15, inland fisheries grew at 7.9%, fetching US $5.5 billion in foreign exchange [2]. But aquaculture farming requires lot of care, including periodic observations of the weather, water quality and feed consumption. Drop in feed consumption, coupled with low temperature, may be an early indication of a disease. In FY13-14, shrimp production fell in Southeast Asian countries due to spread of Early Mortality Syndrome (EMS) disease, reducing export by 50% [3]. Hence farm data is crucial for daily data driven crop health monitoring and management. But it's very difficult to manually assimilate such bulky data and extract information impacting real-time decision making. This is especially challenging when each farmer manages multiple ponds, spread out over a distance and with no or low speed data network. mKRISHI® collaborated with farm managers, government regulators and farmers to develop \"mKRISHI® -AQUA\" service, in an iterative, multi-phase development process. This service helps in data collection, compilation and presentation of the patterns in visual format, enabling decision on further operations (such as feeding) in a more real-time manner compared to paper based operation.","PeriodicalId":214922,"journal":{"name":"Proceedings of the 7th Indian Conference on Human-Computer Interaction","volume":"133 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 7th Indian Conference on Human-Computer Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2835966.2836277","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Besides meeting the domestic needs of cheap animal protein, Indian fisheries, is source of livelihood for 14.5 million fishers [1]. During FY2014-15, inland fisheries grew at 7.9%, fetching US $5.5 billion in foreign exchange [2]. But aquaculture farming requires lot of care, including periodic observations of the weather, water quality and feed consumption. Drop in feed consumption, coupled with low temperature, may be an early indication of a disease. In FY13-14, shrimp production fell in Southeast Asian countries due to spread of Early Mortality Syndrome (EMS) disease, reducing export by 50% [3]. Hence farm data is crucial for daily data driven crop health monitoring and management. But it's very difficult to manually assimilate such bulky data and extract information impacting real-time decision making. This is especially challenging when each farmer manages multiple ponds, spread out over a distance and with no or low speed data network. mKRISHI® collaborated with farm managers, government regulators and farmers to develop "mKRISHI® -AQUA" service, in an iterative, multi-phase development process. This service helps in data collection, compilation and presentation of the patterns in visual format, enabling decision on further operations (such as feeding) in a more real-time manner compared to paper based operation.