The need

Cricket is an old sport with a dedicated following of fans across the globe. With a surge of interest in the game, professionals and amateurs are looking for ways to improve the quality of their game.

The idea

Players want data-driven assistance to improve the quality of their play. Spektacom uses sensor technology on cricket bats to harness data from real play, then creates insights from cloud-powered data analytics, machine learning and AI.

The solution

The sensor sticker captures data and analyses impact characteristics through wireless sensor technology and cloud analytics. The data is analysed with AI models developed in Azure and transferred to the edge for continuous feedback.

Technical details for Spektacom

Power Bats use an innovative sensor-sticker that measures the quality of a player’s shot by capturing data and analysing impact characteristics through wireless sensor technology and cloud analytics. This unique non-intrusive sensor weighs less than five grams and is stuck behind the bat. Performance stats are used to return data-driven feedback to players and coaches.

The data from the Power Bats is analysed with powerful AI models developed in Azure and transferred to the edge for continuous feedback to the player. In professional games, the sticker communicates using Bluetooth Low Energy (BLE) with an edge device called Stump box that is buried behind the wicket. The data from the stump box is transferred and analysed in Azure and shot characteristics are shared with broadcasters in real-time.

Given that cricket stadiums have wireless access restrictions and stringent security requirements, to ensure secure communication between bat, edge device and Azure, Stump Box is powered by a Microsoft Azure Sphere-based hardware platform.

In the case of amateur players, the smart bat pairs with the Spektacom mobile app to transfer and analyse sticker data in Azure. The solution is powered by Azure Sphere (Stump box), Azure IoT Hub, Azure Event Hub, Azure Functions, Azure Cosmos DB and Azure ML 2.0.

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