Pawel Skiba
Smart, Connected, Unexpected: The Wild Side of IoT and AI
#1about 4 minutes
Understanding the complexities of IoT hardware development
IoT hardware development involves a long and difficult process of designing, testing, and certifying physical devices like PCBs, unlike the faster iteration cycles of software.
#2about 4 minutes
Building smart rodent traps for warehouse management
An IoT solution uses sensors and LoRa connectivity to monitor thousands of rodent traps in warehouses, automating a difficult and manual maintenance task.
#3about 3 minutes
Applying computer vision to automate insect counting
An IoT device with a camera and edge computing automates the tedious job of identifying and counting insects on sticky traps in clothing production facilities.
#4about 4 minutes
The engineering challenge of monitoring septic tanks
Developing a reliable sensor to measure septic tank levels is a difficult R&D project due to the harsh environment, unpredictable surfaces, and connectivity issues.
#5about 3 minutes
Using thermal cameras to investigate household pests
A practical application of thermal imaging reveals that mysterious nightly sounds in a house were caused by martens living in the roof, not ghosts.
#6about 4 minutes
Counting people with thermal cameras for compliance
During the pandemic, a GDPR-compliant people-counting system was developed using thermal cameras and computer vision to enforce occupancy limits in public spaces.
#7about 3 minutes
The difficulty of detecting fevers with thermal cameras
Thermal cameras are unreliable for fever detection because they measure skin temperature, which varies greatly, making it a complex AI challenge to correlate with actual body temperature.
#8about 1 minute
Key lessons learned from years of working in IoT
The speaker shares key takeaways, including the unreliability of thermal cameras for fever detection and the vast, unexpected opportunities for automation.
Related jobs
Jobs that call for the skills explored in this talk.
Matching moments
27:25 MIN
Showcasing computer vision project examples
Computer Vision from the Edge to the Cloud done easy
33:59 MIN
Future applications and positive public reception
Fighting Fraud with an AI Grandma - Ben Hopkins and Morten Legarth from faith @ VCCP
19:16 MIN
Key takeaways on creative software and hardware projects
How to Automate your Murder Mystery
02:27 MIN
Defining AI at the edge and its industry applications
Trends, Challenges and Best Practices for AI at the Edge
11:05 MIN
Real-world robot deployments and their challenges
Robots 2.0: When artificial intelligence meets steel
17:21 MIN
Addressing European skepticism by demystifying AI's value
How to build a sovereign European AI compute infrastructure
20:07 MIN
Encouraging creative coding and hardware experimentation
How to Automate your Murder Mystery
08:58 MIN
Why robotic capabilities are advancing so rapidly
Robots 2.0: When artificial intelligence meets steel
Featured Partners
Related Videos
The AI-Ready Stack: Rethinking the Engineering Org of the Future
Jan Oberhauser, Mirko Novakovic, Alex Laubscher & Keno Dreßel
Breaking the Hardware Mindset: Overcoming Barriers to System-Level Innovation
Réka Leisztner
Robots are coming into the wild! Full-Stack Robotics Engineers, be ready!
Falk-Moritz Schaefer
Robots 2.0: When artificial intelligence meets steel
Thomas Tomow
Bringing AI Everywhere
Stephan Gillich
Strange New Worlds: shaping the future of the digital age
Andreas Kaldun
Bringing the power of AI to your application.
Krzysztof Cieślak
Trends, Challenges and Best Practices for AI at the Edge
Ekaterina Sirazitdinova
From learning to earning
Jobs that call for the skills explored in this talk.


Student project: Optimizing Open-set Recognition Methods for Reliable Real-world AI Systems
Imec
Azure
Python
PyTorch
TensorFlow
Computer Vision
+1








IoT
Kontron AG
Canton de la Garde, France






Hardware Engineer - Robotics (Competitive) at Well-funded intelligent robotics company
Jack & Jill\u002FExternal ATS
Charing Cross, United Kingdom




