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 in applying big data for retailers: building big data solutions and cloud-native platforms.
Our client’s end customer is a supermarket chain operator running 83 stores in Estonia, 125 in Latvia, and 56 in Lithuania, along with logistics operations, supply chains, and distribution centers in the region. The challenge they were facing is common to many retail operators — suboptimal monitoring of refrigerator and freezer equipment. Discovering issues with refrigeration equipment too late can lead to thousands of dollars’ 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.
In the summer of 2018, the end customer decided to implement our client’s 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 and provide stable Wi-Fi coverage for the end customer’s largest supermarket, which is 3 kilometers in length and 8,800 square meters in area. Once the system was installed, however, it had to extract and transfer data in real time to make it useful.
Having built a robust big data analytics platform able to collect big data for retailers from hundreds of sensors across 125 stores in Latvia, our client’s 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 in spoiled food stocks.
The solution delivered by Intellias is a cloud-based IoT platform for predictive equipment maintenance that’s powered by analytics tools aimed at processing big data for retailers’ usage. Intellias also built a convenient dashboard where the company can monitor the performance of its assets. One of the first results was the discovery that the outsourced management company ran the refrigerators in some stores at -30°C, which is 10°C lower than the requirements of the European food storage safety guidelines. Adjusting the temperature helped the end customer save around 20% on energy consumption for those stores.
Intellias built a robust big data platform that analyzes the signals from thousands of temperature sensors in real time and informs store managers at once if a refrigerator starts malfunctioning. This has allowed the end customer to save time, money, and effort as well as to ensure compliance with regulatory requirements while providing precise and timely information on equipment performance across the whole supply chain.
In addition, all data is securely stored in the cloud, enabling simple auditing and traceability. Our client was very satisfied with the solution delivered and is currently in negotiations to expand the system to other countries across the EU. Intellias has added this successful case to its big portfolio of big data case studies retail industry requires.