Typical IoT applications are data rich and attention poor: they must be able to follow the age-old rule of good design—“do what the user expects”—based on contextual data, instead of direct commands from users. Because of these constraints, IoT designs are powerful and intuitive only to the extent that their data architectures are capable of faithfully expressing user intent.
This session shares principles for building effective intention-aware data architectures. I draw on examples (good and bad) from across the industry, as well as personal experience at Jawbone and Metta.
Geared toward the practical needs of product development, this talk will address:
More broadly, this talk brings together two active conversations in the IoT community—interaction design and data architecture—and argues that they should be the same conversation. The intention layer is the point of contact between the two approaches.
The presentation does not include a live demo, and no special expertise is required.
Abe Gong is fascinated by the intersection of data science, behavior change, and the Internet of Things. Prior to co-founding Metta, he was the first data scientist at Jawbone, and lead data scientist at Massive Health.
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