Combining AI and IoT
summary
Argues that AI is required to turn IoT’s flood of sensor data into action and shows a working stack: carrier-agnostic SIM cards with static IPs, VPN and REST API, a cloud AI platform for real-time analysis and device control. Demonstrations include Arduino + GSM + pulse sensor for elderly monitoring (code on GitHub), a shipping-container tracker with IBM, and a river trip tracker that uses 20 MB in 12 days. Company scale: ~50 staff, access to 400 mobile networks and global coverage.
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chapters (24)
- 0:00Intro
- 3:56Artificial intelligence
- 6:32The biggest source of data on the planet
- 9:15Multi-Network Solution for lot
- 10:59Five Helpful Questions
- 12:33Need: Connection Quality
- 12:54Need: Advanced Security
- 13:27Need: Access to the Device
- 13:45Need: Flexibility
- 14:12Need: Control and Automatization
- 15:12Implementation in the lot projects
- 15:41One VPN Tunnel for All Devices
- 16:27wherever SIM platform
- 17:07Patching loT device via API
- 17:29Natural Language for the lot
- 18:17Easy Implementation of E-Health Monitoring
- 19:59Sketch for Arduino + GSM
- 20:25Alarm systems
- 21:19Tracking for a nature conservation project
- 22:28Secure data transfer via SMS in case of poor GSM coverage
- 25:56Automotive / Telematics
- 27:09Agriculture Industry
- 28:13Energy Saving
- 29:04Increasing Sensing Quality of Life
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