Our client’s goal was to significantly reduce the amount of time it took for their system to process data from its complex sensor network and visualize that data for their end customers.
The Company’s Challenge
Our client’s goal was to significantly reduce the amount of time it took for their system to process data from its complex sensor network and visualize that data for their end customers. At its current configuration the retail store owner had to be in front of the machine to interact with the data and lacked access to data in real-time because batch analysis took 24 hours to process. Additionally, they lacked access to simplified monitoring tools especially when monitoring and managing multiple locations, as well as each new implementation required similar amounts of work to spin up at each new location.
Clovity’s Solution
Clovity leveraged it’s Studios’ deep understanding of complex IoT systems, Analytic Platforms, Real-Time data visualization techniques, data storage, and our extensive experience in the Retail market to upgrade our client’s system to ensure up to the moment tracking of all aspects for their end-client’s locations.
The solutions required a three pronged approach to ensure the functionality that our client’s customers desired to run their businesses in real time. Our first step was to create a iOS and Android application where store owners can monitor and analyze the flow of cars through the drive-thrus of their restaurants. Alerts on large customer volumes of 10 or more cars, precise totals of customers utilizing the drive thru in a 24 hour period, multiple restaurant location tracking centralized on one application, and real time push notifications allowing them to interface with the system quickly, were all new features that were added to build out our client’s product offering. This first step began to offer the ability to manage store utilization, provide better customer service, and accelerate data analysis and monitoring capabilities.
The second prong of this project required Clovity to reduce the amount of time the DTDS process, which is the process of accepting data and sending it to the Azure cloud, by modifying their CU 50 sensor product to send expandable card data to Azure directly rather than coming in via the DTDS. This helped to significantly reduce the refresh interval and time gap between actual data and real time data to enable up to the moment monitoring. Clovity reduced this time by 75%, from 20 seconds down to 5 seconds.
The third part required Clovity to build a web interface that monitors if the system is working correctly remotely. It can monitor all CU50 devices, gateways, and PUCs for optimal system diagnostics. The PUC was a sensor that denotes cars passing through a certain area, while the CU50 would communicate with these devices and collect data from numerous PUCs. The CU50 would then pass that information along to the gateway and up to the cloud. A large challenge was configuring the frequency for the CU50/40, the report rate, the sample rate and the baseline filter to accommodate. Each location needed to be manually configured posing a significant logistical challenge for implementation. All data had to be localized at the store location.
In order to make these actions remote, Clovity created the ability for the CU50 data to quickly be transmitted to the cloud so that it could be monitored by owners and managers in real-time regardless of their location. The PUCs were now able to be monitored remotely by utilizing the UI Web Page Interface that Clovity’s team had created. With this added functionality, store managers were able to optimize resources to deliver optimal customer service as well as diagnose any network issues remotely.
Through their partnership with Clovity our client was able to take their product to the next echelon of connectivity and enable it to all occur in real time. By reducing the latency in their system, our client’s customers can now manage their business effectively from anywhere with a connection.
via https://www.AiUpNow.com
October 5, 2021 at 08:42AM by IoT Now Magazine, Khareem Sudlow
