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Expert source: Proximity detection in contact tracing

UC San Diego electrical engineer Dinesh Bharadia is available as a source to answer questions about proximity detection in contact tracing apps, particularly in more challenging indoor environments.

Dinesh and his research team specialize in determining robust and precise locations indoors, and have developed algorithms based on WiFi and Bluetooth data to much more accurately do so. Many contact tracing apps rely on Bluetooth Low Energy (BLE) technology, which has a range of 150 feet. This can be problematic, particularly indoors, where it’s difficult to tell if users are separated by a wall or divider—an app might consider neighbors separated by a wall as “in contact” with one another, for example. 

Dinesh and his team have incorporated algorithms to avoid this issue into their own contact tracing app called BluBLE, which delivers a more accurate personalized risk of contact score.

Dinesh can answer questions about proximity detection, contact tracing apps, or his app BluBLE.

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UC San Diego electrical engineer Dinesh Bharadia is available as a source to answer questions about proximity detection in contact tracing apps, particularly in more challenging indoor environments.

Dinesh and his research team specialize in determining robust and precise locations indoors, and have developed algorithms based on WiFi and Bluetooth data to much more accurately do so. Many contact tracing apps rely on Bluetooth Low Energy (BLE) technology, which has a range of 150 feet. This can be problematic, particularly indoors, where it’s difficult to tell if users are separated by a wall or divider—an app might consider neighbors separated by a wall as “in contact” with one another, for example. 

Dinesh and his team have incorporated algorithms to avoid this issue into their own contact tracing app called BluBLE, which delivers a more accurate personalized risk of contact score.

Dinesh can answer questions about proximity detection, contact tracing apps, or his app BluBLE.

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