Keysight Technologies Ensures Optimal Battery Life in Mission Critical and Consumer-Based IoT Devices

New solution enables IoT designers to detect design weaknesses accelerating troubleshooting and design verification

Keysight Technologies a leading technology company that helps enterprises, service providers, and governments accelerate innovation to connect and secure the world, today introduced the X8712A IoT Device Battery Life Optimization software solution, to ensure optimal battery life prior to devise deployment to accelerate troubleshooting and device verification.

  • Many IoT devices today run on battery power. For mission-critical IoT applications such as those in the healthcare and industrial industries, where lives can be at risk due to premature device failure, battery life is more crucial than ever. The challenge falls to IoT device makers to ensure the battery life of their devices will live up to expectations in the real world.
  • Keysight’s new X8712A solution enables IoT device makers to perform event-based power consumption analysis on IoT devices to gain a better understanding of how IoT devices spend their battery charge when operating in real-world conditions.
  • “IoT device developers face many challenges when accurately estimating and validating their device’s battery life expectancy,” said Ee Huei Sin, vice president and general manager of General Electronics Measurement Solutions (GEMS) at Keysight Technologies. “Keysight’s new solution has been designed specifically for these device makers to ensure optimization of their battery-powered IoT devices, while validating that they work as expected in all applications.”

The Keysight IoT Device Battery Life Optimization solution offers IoT device makers the ability to:

  • Detect design weaknesses with a wide-dynamic-range current measurement and fast 20-µs sampling rate to capture an IoT device’s dynamic current consumption for a specific radio frequency or direct current event. It then automatically correlates that event to the device’s current consumption to easily identify the subsystems or events requiring optimization.
  • Optimize battery life by calculating the RF or DC event’s occupancy time and current consumption contribution in percentage. By specifying the battery capacity and area of interest, the software estimates battery life based on the device’s charge consumption, so necessary steps can be taken to improve battery life.

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