{"id":26798,"date":"2020-08-21T15:54:12","date_gmt":"2020-08-21T13:54:12","guid":{"rendered":"https:\/\/www.intellias.com\/?p=26798"},"modified":"2024-07-10T15:26:38","modified_gmt":"2024-07-10T13:26:38","slug":"big-data-for-retailers-a-platform-for-equipment-monitoring-in-supply-chains","status":"publish","type":"post","link":"https:\/\/intellias.com\/big-data-for-retailers-a-platform-for-equipment-monitoring-in-supply-chains\/","title":{"rendered":"Big Data for Retailers: A Platform for Equipment Monitoring in Supply Chains"},"content":{"rendered":"
A wireless sensor vendor from the Baltic states turned to Intellias when one of their end clients needed assistance creating a cloud-based real-time big data analytics platform. They entrusted this task to Intellias due to our multiple big data use cases in retail and our retail expertise<\/a> in applying big data for retailers: building big data solutions and cloud-native<\/a> platforms.<\/p>\n Our client\u2019s end customer is a supermarket chain operator running more than 200 stores in Europe along with logistics operations, supply chains, and distribution centers in the region. The challenge they were facing is common to many retail operators \u2014 suboptimal monitoring of refrigerator and freezer equipment. Discovering issues with refrigeration equipment too late can lead to thousands of dollars\u2019 worth of spoiled food overnight, not to mention costly repairs. In most cases, the end customer monitored refrigerator equipment manually, noting temperature regimes on pen and paper so that data was available only after a failure.<\/p>\n <\/p>\n In the summer of 2018, the end customer decided to implement our client\u2019s wireless refrigeration unit monitoring sensors that send temperature data by the minute. The superior quality of those devices allowed a single base station to operate up to 100 sensors<\/b> and provide stable Wi-Fi coverage for the end customer\u2019s largest supermarket, which is 3 kilometers in length and 8,800 square meters in area<\/b>. Once the system was installed, however, it had to extract and transfer data in real time to make it useful.<\/p>\n Having built a robust big data analytics big data for retailers from hundreds of sensors across 125 stores in the EU, our client\u2019s end customer achieved greater process optimization and automation. The platform instantly alerts staff should any sensors detect temperature fluctuations outside the optimal range. In this way, store managers are alerted the very minute a fridge goes out of order, giving them ample time to relocate groceries to another unit and order repairs. As one of the big data use cases in retail, this solution has helped save millions of dollars<\/b> in spoiled food stocks.<\/p>\nSolution delivered<\/h2>\n