Estimating battery life for IoT devices has always been challenging. You need seamless ranging, fast bandwidth, and event-based power analysis just to get started. But real-world IoT devices don’t always behave in predictable ways. They have to adapt and respond to environmental changes, RF interference, and demands from other devices, especially in contexts such as mesh networks and load-balancing edge computing architectures. How can you possibly begin to estimate battery life in such contexts?
• What the key challenges are in estimating battery life
• How IoT devices face challenges that are difficult for traditional tools
• When slow measurements are better than fast ones
Senior Application Engineer
Brad Jolly has been with Keysight Technologies (previously Hewlett-Packard and Agilent Technologies) for more than 24 years, including roles in software R&D, UI design, learning products, application engineering, product support, training, product marketing, and product management. He currently works as an applications engineer focusing on IoT solutions. He received his B.S. in Mathematics from the University of Michigan.
Business Development Manger
Julien Sarrade is responsible for IoT Business Development activities at Keysight Technologies, bringing solutions to help electronic design and validation engineers solving their toughest Test & Measurement challenges. Healthcare wearables, smart home and smart city are examples of domains in which power consumption, wireless connectivity and coexistence are hot topics to be addressed to successfully bring a product to the market. In each specific case, Julien helps customers finding the right balance between severity, time and cost of test. Prior to joining Keysight, Julien has worked for more than 10 years in the mobile networks’ ecosystem. Julien holds a Master degree in Wireless Telecommunications from Telecom Lille in France.