IOT Flashcards
(84 cards)
Iot devices, such as sensors and actuators,
collect data from their environment.
Data collection –
Devices that detect and measure physical
properties.
Sensors:
Using communication protocols like
Wi-Fi, Bluetooth, and cellular networks to send data to a
central system.
Data Transmission:
Temperature Sensor is a device that measures
Temperature or heat energy and converts it
Into electrical signal that can be read by monitoring system.
Thermocouple
MotionDetector
Is a device that detects movements
Within a specific area and triggers
An action, such as turning on lights, sounding
Alarm, or sending a notification.
A PIR (Passive Infrared) Sensor
Some data processing is done locally on the device or nearby edge severs to reduce latency and
bandwidth usage. This can include filtering, aggregation, and preliminary analysis.
Edge Processing:
More complex processing tasks are often handled in the cloud, where powerful servers can
perform advanced analytics, machine learning, and data integration.
Cloud Processing:
Data can be stored locally on the device or edge servers for quick access
and low latency requirements.
Local Storage:
For scalability and long-term storage, data is often stored in cloud
databases and data lakes. Cloud storage provide the flexibility to handle large volumes of
data and supports various data management and retrieval operations.
Cloud Storage:
refers to the large amounts of data generated by Iot devices like sensors and
cameras.
Big data
Iot devices collect data from their surroundings. For example, a temperature sensor records temperature readingsData Collection
Data Collection
This data is stored in large databases, often in the cloud, which can handle
huge amounts of information.
Data Storage
The stored data is analyzed to find used useful patterns and insights. For
example, analyzing temperature data predict weather changes.
Data Analysis
Some data is processed immediately to make quick decisions, like
turning on a fan when it gets too hot.
Real-time Processing:
Helps Iot Systems learn from the data they collect and make smart decisions.
Here’s how ML is used in Iot:
Machine Learning (ML) In Iot
ML can predict when machine might break down, maintenance can
be done before it fails.
Predictive Maintenance
ML can spot unusual patterns in data, which might indicate a problem,
like a security threat.
Anomaly Detection:
: ML can automate tasks based on data, reducing the need for human
intervention. For example, automically adjusting lighting based on room occupancy.
Automation:
ML can tailor services to individual preferences, like recommending music
based on listening habits.
Personalization:
ML can improve the efficiency of Iot systems, like optimizing energy use in
smart homes.
Optimization
Using data from various sensors manage traffic, save energy,
enhance public safety.
Smart Cities:
Monitoring patient data in real-time to provide personalized treatments
and early detection of health issues.
Healthcare:
Improving manufacturing processes through predictive maintenance
and quality control.
Industrial Iot:
s a combination of
computer hardware and software designed for a
specific task
embedded system
