1. Remarks by Dr Mawaki Chango Kara University DigiLexis Consulting
The Internet of Things
Remarks by Dr Mawaki Chango
Kara University DigiLexis Consulting

2. Definition
“Internet of Things”: Coined in 1999 by Kevin Ashton a British technology pioneer
Context of RFID ( Radio-Frequency Identification tags)
Connecting objects, including everyday items, to the Internet using sensors.
Definition:
Network connectivity
Computing capability
Objects including sensors and items not generally considered computers
Generating, exchanging and consuming enormous data with minimal human intervention

3. Connectivity models
March 2015: IAB released architectural guideline (RFC 7452) for networking of smart objects
Device-to-Device
Device-to-Cloud
Device-to-Gateway
Back-End Data-Sharing

4. Device-to-Device Home automation scenario
Light switch / Light bulb
Thermostats
Door locks
Direct communication over various networks, incl.
IP networks
Bluetooth
Z-Wave
ZigBee

5. Device-to-Cloud
Device connects directly to and can exchange data through the cloud
Wired Ethernet or Wi-Fi to connect the device to the IP network and ultimately to the cloud service

6. Device-to-Gateway Device-to-application-layer gateway (ALG) model
IoT device connects through an ALG service as a conduit to reach a cloud service
Consumer devices
Smart phone running an app
Communicating with a device (e.g., personal fitness tracker)
Relaying data to a cloud service

7. Back-End Data-Sharing
Enables users to export and analyze smart object data from a cloud service in combination with data from other sources
Supports granting access to the uploaded sensor data to third parties
Extends the single device-to-cloud communication model and helps avoid data silos (IoT device uploading data only to a single application service provider.)

8. IoT Issue Areas Security Privacy Interoperability/ Standards
Legal, Regulatory and Rights
Emerging Economy and Development Issues

9. Security
The more devices are interconnected, greater the vulnerability
Network security threats also have network power – local risks (security vulnerability) may quickly go global
Smart utility power meter
Implanted pacemaker
Network (negative) externalities
Security is function of risk level, potential threats.
How can regulation help minimize the risks related to commercialization of devices with known or unknown security flaws?

10. Privacy IoT may challenge traditional expectations of privacy
User’s privacy expectations vs. Scope and use of the data by data collector
Multiple devices = Multiple data sourcing points = Multiple data streams
Combining different data streams may give invasive insights about the user
Increasingly consumer devices record sounds and pictures from their environment

11. Legal, Regulatory and Rights
Data protection and crossborder data flows
Collected data may be beneficial as well as detrimental to the user (when it is used in a discriminatory way)
Increasing use of IoT devices in legal actions: What are the implications for legal evidence, the manufacturers and for the society?
which legal regime governs the device collecting the data, and which governs the storage and use of the collected data? This scenario also raises normative questions. Can these laws be modified to reduce the degree of Internet fragmentation they cause while still protecting the rights of users? Should a jurisdiction with more-restrictive data protection laws for handling and transmission of certain IoT-enabled data be able to project those legal requirements onto other jurisdictions?

12. Emerging economy - Development
Needs will shape opportunities, meaning the IoT potential is significant for developing economies
Water quality and use; waste management; disease and health; natural resource monitoring; climate change; food security; etc.
Particularly: IoT-enabled “smart agriculture” techniques are envisioned across the entire value chain to improve the sustainability and productivity of the food supply.
For example, the application of sensor networks to environmental challenges, including water quality and use, sanitation, disease, and health, climate change, and natural resource monitoring, could have significant impact beyond resource management. The data derived from such applications also could be used in research contexts, assisting local scientists and universities in making unique contributions to the broader body of global scientific knowledge and providing an incentive for local academic talent to stay in country to conduct research

13. Recap Definition Connectivity models Issue areas
Source: The Internet of Things: An overview. Understanding the issues and challenges of a more connected world. ISOC, October 2015

14. Thank you for your attention!
Dr. Mawaki Chango
Kara University
DigiLexis Consulting
@mawakichango