Emerging Technologies
Domain scope
Emerging technologies examines AI, IoT, cloud, big data, blockchain, VR/AR and 5G, with emphasis on capabilities, limitations and social impact. Questions ask you to select an appropriate technology and justify it.
Core rules
- Cloud service models: IaaS supplies virtual machines and storage; PaaS supplies a development and runtime platform; SaaS supplies finished applications. Deployment models include public, private, hybrid and community.
- IoT includes sensors or actuators, connectivity, processing and a user interface. Constraints include power, bandwidth, security and physical exposure.
- AI and machine learning differ: ML is a subset of AI that learns patterns from data; generative AI produces content but can hallucinate.
- Blockchain is a distributed ledger; immutable means very difficult to alter, not absolutely impossible. Consensus and cryptography support trust without a central authority.
- Big data characteristics are often summarised as volume, velocity, variety, veracity and value.
Worked example
A school wants a timetable system with no server maintenance and minimal coding. Choose IaaS, PaaS or SaaS. Reasoning: SaaS is the best fit because the school uses a ready application over the internet while the provider manages servers, runtime and updates. PaaS would require development effort; IaaS would require the school to manage operating systems and applications. Trade-offs include less control and data-residency or exit risks.
Traps
- Defining cloud computing as simply using the internet; cloud involves on-demand, measured service.
- Treating AI and ML as synonyms.
- Claiming blockchain makes data legally true; it only records what was entered.
- Ignoring IoT security: default passwords and unpatched devices are common weaknesses.