Convenience store inside sales continue to rise, according to the 2021 Convenience Store News industry report. While hot food and cold beverages are a major part of that growth, keeping things cold, fresh, hot, and stocked is a major undertaking through purely manual inspection.
With over 850 convenience stores and gas stations along the East Coast of the United States, Wawa is the 29th largest privately held company by revenue according to Forbes. keeping an eye on replenishing coolers and hot serve bins with fresh product was nearly impossible for their store clerks. That challenge and solution is the subject of Techolution’s latest blog post.
Monitoring beverages and hot food items is not an uncommon problem for all convenience store chains. Clerks can only check so many times a day while ensuring that customers get served. Wawa has 14 different fresh breakfast sandwiches, burritos, and hash brown products in high demand. They needed to avoid lost sales and spoilage of items that had a defined and short shelf life. WaWa is a company built on a history of change and technological innovation. The IT leadership knew there must be a digital solution.
Techolution’s latest Case study shows how they partnered with Wawa to develop and move past a proof-of-concept (POC) computer vision solution. The business outcomes-driven cloud, AI, DevOps, and IoT-driven solution would enable them to have constant digital eyes on coolers and hot food bins. This would ensure clerks know exactly when to restock so they could provide the freshest hot sandwiches and coldest beverages.
The case study shows how Techolution planned, designed, and implemented a customized computer vision platform for the Wawa POC. Four carefully positioned cameras would provide real-time and accurate alerts to warmer and cooler restocking needs. The relevant data images would be sent to the custom-built Techolution Google cloud platform via Wi-Fi and an edge gateway device for data aggregation.
Once processed, the application sends the processed real-time data back to the store via a custom dashboard. Employees can see what products need restocking in real time from a central location.
The case study explores the benefits and challenges of developing a computer vision platform. As a subset of AI, the algorithm governing the sending of accurate and timely image data had to be balanced with accurate physical placement and aiming of cameras for both coolers and warmers. Having partnered with many enterprises on AI projects, Techolution has developed a proprietary approach to AI projects that ensures faster and more accurate application-based AI algorithms that evolve to deliver greater business value.
There are countless uses of computer vision, and every solution is a custom project. Because of Techolution’s highly skilled AI, cloud, IoT and AppDev teams over a growing roster of varied successful projects experiences, innovation and adaptability were standard operations. The case study shows how they worked in collaboration with the Wawa team to deliver predictive stocking alerts via an intuitive dashboard for store clerks.
Overcoming challenges like automatic deletion of patron extremity and potential PII data was just one aspect of algorithm development. The final algorithm could detect these anomalies. This ensured that the system only sent clean image data to the cloud before being configured in table access form in the onsite dashboard.
Techolution has always differentiated their expertise, innovation, and business outcomes in the AI, IoT, Cloud, and DevOps digital transformation spaces. This is punctuated by their business culture of developing highly skilled and experienced teams that can work together and partner with clients.
The digital transformation company’s dedication to cost effectiveness without sacrificing successful outcomes can be seen in their project proposals like the WaWa project origin. Techolution provides a blanket proposal that allows them to add as many experts across disciplines as the project needs.
This is in stark contrast to other consulting and development firms that charge for each individual expert in their proposals. The proposal and the case study show that this project involved a team comprising 14 developers, engineers, and UX designers across AI/CV, DevOps, IoT, and security.
Among the many and growing business outcome benefits that Wawa has seen so far is a 41 percent reduction in spoilage, which translates to major cost savings. With project outcome analysis ongoing, Wawa expects reportable increased sales metrics along with cost savings as time goes on. To learn more about how Techolution and Wawa partnered on this Computer Vision platform and its outcomes, download the case study here.
To learn more about the limitless possibilities of Computer Vision across every industry, download our Computer Vision eBook here.