Fortune 500 Coffeehouse Chain

IoT Sound Intelligence Proof of Concept

Improving accessibility, in-cafe experiences, and operational efficiency

Challenge

A Fortune 500 Coffeehouse Chain had limited insight to in-café sound pressure levels (SPL). The lack of sound data inhibited the retailer’s ability to identify harmful sounds and prioritize strategies to reduce in-store friction. This further impacted their ability to optimize audio-intelligence in cafe designs, make retail operations more efficient through sound data insights, and elevate their overall customer and employee experiences.

Solution

Kopius designed and implemented an IoT Sound Intelligence Proof of Concept (POC). Organizing a team of audio and data architects, hardware engineers, and analysts, Kopius installed IoT devices logging data in an isolated Azure Cloud location. The secure data flowed into a real-time PowerBI Dashboard via Azure IoT Hub and Databricks that measured minimum, average, and maximum sound pressure levels, allowing the Kopius team to capture, analyze, and deliver sound intelligence for the retailer’s in-café experience.

Results

The successful IoT Sound Intelligence POC deployment captured sound data and uncovered business insights that can help shape how the Fortune 500 coffeehouse chain designs future stores while ensuring accessibility for their employees, customers, and partners. The deployment also opened avenues for predictive maintenance and operational efficiency, showcasing the potential of audio innovation in Retail Tech.

Fortune 10 Company

Experiential Marketing Application and Internet of Things (IoT)

Our client had established itself as a leader in enabling IoT technologies. The Internet of Things has grown increasingly complex as virtually any electronic device in any space can be used to collect and use data, resulting in a variety of services and experiences.

Challenge

As more smart home and office solutions enter the mainstream, it’s become difficult for the average, non-tech-evangelist to navigate the sea of hardware, software, and connected hub devices. Our client needed a retail experience that would allow its consumers to touch, feel, and demo smart devices to ensure they meet their needs.

Further the experience needs to showcase the tech company’s brand and showcase its leadership compared to other big brands.

The Solution

Kopius* was engaged to conceptualize, design, build, and deploy an in-person experiential retail experience showcases the connected life experience, which brings the smart home and office to life in a visually stunning, engaging way.

The in-person experience showcases technology and is supported by technology, including web applications and digital demos. The demos bridge the virtual world on screen with the environment around the consumer, showcasing a connected world by immersing the consumer in a connected world.

Customers interact with a mobile device, choosing from a variety of common “smart” scenarios. Once selected, a screen shows the scenario in action while smart light strips in retail cubbies light up the screen according to the products being used.

Technologies used include Microsoft Azure, Blog Storage, Application Insights, LifX Strip Lighting, UWP application development, and Android application development.

Results

The experience is an effective, scalable, and self-guided way for customers to understand how a variety of IoT products can integrate into and improve their day-to-day lives. The retailer sold more product to first- and third-party customers thanks to increased customer confidence and understanding from the demo and experience.

*Kopius performed this work under its previously known business name, Valence.

Fortune 500 Insurance Company

Cloud Enablement and Machine Learning

Insurance companies rely on extensive historical data to predict and manage risk and establish rates. Historical data is becoming less reliable as insurance companies face simultaneous challenges of escalating climate change risks and shifting industry regulations.

Challenge

A prominent insurance company approached Kopius* seeking a way to better predict and plan for weather disasters. Doing so would help improve its risk models and allow more accurate premiums for policyholders. Given the unpredictable nature of many weather events, a solution that gave real-time information about whether a weather event had occurred or was about to occur was important.

The Solution

Kopius was engaged to develop a pilot solution using cloud-based machine learning and IoT devices to identify weather events and notify the client in real-time. We trained the machines to recognize sounds picked up by IoT devices at weather ground stations, using 10,000 audio seed files.

Results

With our algorithms and AI process, we could train the machines to recognize 12 unique types of weather events, including metrics tracking the severity of the events.

The pilot included placing 500 devices with machine learning modes at strategically selected locations nationwide. The input from the devices was found to be 85% accurate in the initial pilot. The pilot informed future strategies for the insurance company and contributed to the technology development roadmap.

*Kopius performed this work under its previously known business name, Valence.

Wood Products & Building Materials Manufacturer

Internet of Things and Data Visualization

This Fortune 500 North American manufacturer and distributor of wood products and building materials enjoys recognition as on of the world’s most respected companies. The company is a leader in its industry, which includes businesses operating with processes that are sometimes more than 100 years old.

Challenge

This client was operating a door manufacturing facility that relied completely on manual processes and functions. While there are benefits to this hands-on approach, there was no way for management to know when machines were idle in the factory, or if the factory is achieving manufacturing goals.

When the project started, output was falling short of production goals by as much as 40%.

The client needed insight into machine operations so it could better manage and predict output and optimize facility performance to better achieve production goals.

The Solution

Kopius* was engaged to design and develop a digital solution that would collect, organize, and visualize operations data for facility operators.

The solution was achieved by implementing IoT sensors on three manufacturing machines. We then used Microsoft Azure to pull data from the controller of a fourth machine.

Additionally, we designed and developed a web application with a Power BI Dashboard to pulled the data from Microsoft Azure. We conducted user interviews and research to validate the reports and visualizations that would be most meaningful to the facility management team.

Results

Gathering real-time data from these manufacturing machines allowed management to measure real-time product output. The visibility to production allowed increased output and higher revenue.

*Kopius performed this work under its previously known business name, Valence.