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Japan\u2019s aging demographics and other factors have made the recruitment of experienced sorters difficult, particularly when so much repetitive work is required. To counter this problem, the university approached its long-term partner company, Toyota Tsusho, which in turn brought in Microsoft Japan to help come up with ways of automating a number of processes. The aim is to relieve workers of manually intensive duties so that they can focus their valuable skills on more demanding tasks.<\/p>\n
This latest innovation centers on software that automatically regulates the flow of water through pumps that transfer fingerlings from their pens and onto conveyor belts for sorting. IoT and AI tools continuously monitor and adjust the flows.<\/p>\n \u201cThere are three processes involved in sorting fingerlings,\u201d explains Naoki Taniguchi, who manages the Institute\u2019s Larval Rearing Division and is Deputy General Manager of the Aquaculture Technology and Production Center. \u201cFirstly, we gather the fingerlings near the mouth of the pump that sucks them along with seawater from the fish pens without injuring them. To do this, we must constantly adjust the pump\u2019s water flow to the conveyor belts. Lastly, we sort them by removing fingerlings that are too small or defective from the conveyor belts.\u201d<\/p>\n Taniguchi said adjusting the water flow from a pump is crucial.<\/p>\n \u201cIf the flow is too fast, too many fingerlings will make it onto the conveyor belts, and our sorting teams\u00a0won\u2019t be able to keep up, and some fish that should be removed will be missed. If the flow is too slow, too few fingerlings will be sorted, and production will fall short. Until now, it\u2019s been a process entrusted only to a few operators with sufficient experience.\u201d<\/p>\n The new automated transfer system was created with Microsoft Azure Machine Learning Studio using image analysis technology that recognizes the changing ratio of fish shapes and vacant areas within a pump\u2019s pipes. From this, the system machine-learned how expert human operators adjust flows optimally.<\/p>\n Field tests started last year, and within six months the system achieved the same flow control results as an operator.<\/p>\n Taniguchi said employees, who often used to spend their whole working day just adjusting water flows, are now able to devote their time to applying their rich experience in streamlining other fish farming processes. They will also be able to pass on their technical knowledge to a new generation of aquaculture specialists.<\/p>\n He hopes greater automation will make jobs in the sector more attractive to younger workers looking to build careers.<\/p>\n \u201cJapan\u2019s fishing industry employs about 150,000 people. But 80 percent of them are more than 40 years old. It is vital that we attract young people to the industry,\u201d he said. \u201cThis automatic transfer system is just the beginning of our journey. Ultimately, we aim to automate the sorting process itself as well.\u201d<\/p>\n![\"\"](\"http:\/\/www.sickgaming.net\/blog\/wp-content\/uploads\/2019\/03\/new-ai-and-iot-solution-frees-skilled-fish-farming-workers-in-japan-to-focus-on-more-demanding-tasks-1.jpg\")
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