Stuck between cloud AI and hand-coding for the extreme IoT edge?
The decision for where best to implement sensor processing and AI analytics is shifting from the cloud to distributed approaches.
Cloud based analytics introduces issues of network latency, bandwidth constraints, low fault tolerance, security and data privacy.
Processing at the extreme edge offers the immediacy of real-time insight at the sensor source. But it also requires algorithms that can fit within very limited embedded processor memory, power, and computing headroom relative to the cloud.
This whitepaper explains the trade-offs of centralized cloud AI and extreme edge IoT endpoint processing. It also introduces a new solution, SensiML Analytics Toolkit, that overcomes the challenges and complexity of building algorithms for distributed endpoint IoT processing.
Learn how SensiML Analytics Toolkit can get your IoT sensor application out of the clouds.