IoT project for coffee machines and data analysis for service reasons
Collecting data about coffee machines and their engines.
Planning and predicting service periods.
Analyzing data about engines and sending it to the back office.
Monitoring how engines are performing and what can be improved.
Automatization of business processes
The coffee machine manufacturer wanted to gather and analyze data about the usage of their coffee machines in coffee shops. This would allow them to provide on-time service, collect important data about the machines and their engines, and perform in-depth analysis in their back office.
By using the cloud-based system, the manufacturer should have access to a wealth of data about their machines, enabling them to make data-driven decisions and improve the overall experience for both the coffee shops and their customers. With the ability to monitor and analyze the usage of each machine, the manufacturer would be able to provide high-quality service and keep their machines running smoothly for years to come.
The challenge was in connecting coffee machines with the cloud and collecting data. The ability to gather real-time data about the usage and performance of each machine is essential for improving the customer experience, providing efficient maintenance, and making informed decisions about the future of the products. The cloud-based system must be secure and reliable, with the ability to store large amounts of data and provide access to the manufacturer's back office for analysis. The system must also be easy to use, with a user-friendly interface and intuitive navigation that allows the manufacturer to quickly and easily view the data they need.
We were able to build the bridge to connect data from machines into the cloud and aggregate it for the back office for analysis and monitoring.
We developed a cloud-based system to receive and store the data from the machines.
Created an interface that allows the client to view their machine usage data, schedule maintenance and request service if necessary.
Set up automatic alerts to notify the client of potential issues, based on the data collected.
Analyzed the collected data to identify trends and patterns, and used this information to make recommendations on the improvement of the coffee shops, enhance customer experience, and optimize the maintenance process.
Offered remote access to the coffee shops, allowing them to customize machine settings, make modifications to the brewing process and experiment with different coffee recipes.
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