Tackling the Challenges of IoT and AI - Quality Engineering and Skills
summary
Claims that IoT and AI mainly change scale not basics, producing a fast scaling effect of connected twins and data; key challenges are heterogeneity, long lifetimes, and security. Variants explode—one estimate cites two million variants to test a single device—so test everything is impossible. AI behaves as a black box, raising ethics and unexpected behavior. Recommended actions are shift left quality engineering, model‑based and automated testing, field monitoring, product certification and the planned "Certified Professional for IoT" course (ASQF/GTB).
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chapters (16)
- 0:00Introduction
- 3:17What is IoT
- 5:44Characteristics of IoT
- 8:37Slides
- 8:58Challenges
- 10:26Usage Profiles
- 11:28Variants
- 12:38Passwords
- 13:55Concerns
- 14:56Security
- 16:05AI
- 17:36Summary
- 17:59Phantom Menace
- 18:31Quality Aspects
- 27:49Skills Certification
- 29:24Conclusions
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