Core Concepts
Benefits of ML
Real World Applications
Considerations
Youngs Category
100

Devices like smart thermostats and fitness trackers that collect and transmit data are known as these

IoT Devices

100

Using ML with IoT allows systems to act without human intervention, known as this

Automation

100

ML + IoT used in on body devices to monitor heart rate and detect anomalies

Wearables

100

Risk of personal information misuse from IoT data collection

Privacy and Security

100

The most common cause of computer problems, also known as “ID ten T” error.

ID10T

200

A type of AI that improves performance using data without being explicitly programmed

Machine Learning

200

ML helps IoT systems forecast future outcomes (e.g., equipment failure), called this

Predictive Analytics

200

Smart traffic systems that adapt to congestion using data and ML

Smart Cities

200

Protecting IoT devices and ML systems from hacking is this concern

Cybersecurity

200

This battery percentage causes immediate panic, even though you could probably survive another hour.

10%

300

The process where IoT devices send data to a central system  for analysis

Cloud Processing

300

Smart homes adjusting appliance use based on habits is an example of this benefit

Energy Optimisation

300

Sensors on machines that predict breakdowns before they occur

Predictive Maintenance / Diagnostics
300

ML models can make unfair decisions due to biased training data

Bias or Algorithmic Bias

300

This is what you blame when you lose a game, instead of your skill level.

Lag / Latency / Packet Loss

400

The type of data commonly collected by IoT devices (e.g., temperature, motion, heart rate)

Sensor or Environmental Data

400

ML + IoT can improve this in industries by detecting faults early and reducing downtime

Reliability / Diagnostic

400

Farms using sensors and ML to optimise watering and crop growth

Agricultural Technology and Application

400

Managing and storing large volumes of IoT data is this challenge

Cloud storage / Big Data / Data Management

400

Most common excuse when a student didnt do the assignment and is looking for a way out

Computer Crashed / I lost my document / It got corrupted

500

The key difference: IoT collects data, while this technology extracts patterns and insights

Machine Learning / Artificial Intelligence

500

The ability to analyze massive streams of IoT data quickly is known as this capability

Big Data / Real Time Analysis

500

Security systems that recognise faces or detect unusual behaviour

Biometrics

500

Dependence on reliable internet connectivity for IoT systems

Network Reliability

500

Mr Young's middle name

Johnathon