ELECTRONICS AND COMMUNICATION ENGINEERING (ECE) DEPT

B.E. ECE VI-SEM Subject : Internet of Things(IoT)

Title of Presentation: IoT Enabling Technologies

BY: Lanka Venkata Siva NagaSruthi(2451-22-735-004)

(Under the guidance of Nuli Namasivaya Sir)

 IoT Enabling Technologies: Shaping the Connected World

• The Internet of Things (IoT) is revolutionising industries by seamlessly connecting physical objects with digital systems.
• This integration creates a dynamic network where devices communicate and collaborate, generating unprecedented insights
and opportunities.
• The global IoT market, valued at a substantial $662 billion in 2023, is on a remarkable growth trajectory, projected to reach an
impressive $3 trillion by 2030, underscoring its transformative economic impact.
• With over 15 billion connected IoT devices worldwide in 2023, the scale of this connected world is already immense and
continues to expand rapidly.
 Connectivity: The IoT Backbone
Low Power Wide Area Networks (LPWANs)
Technologies like LoRaWAN and NB-IoT are vital for low-bandwidth applications. LoRaWAN offers a 15km range in rural areas and
5km in urban settings, perfect for smart agriculture or remote asset tracking. NB-IoT excels with over 10-year battery life, ideal for
smart metering and small data packet transmission.

5G/Cellular
5G offers high bandwidth and ultra-low latency, crucial for mission-critical IoT applications. With latency as low as 1ms, it enables
autonomous vehicles and real-time industrial control. Forecasts suggest 2.7 billion 5G IoT connections by 2025, driving advanced
mobility and automation.

Short-Range Wireless
Wi-Fi 6 (802.11ax) significantly boosts network capacity, supporting over 100 devices and quadrupling throughput in high-density
environments like smart factories. Bluetooth Low Energy (BLE) 5.2 provides sub-meter location accuracy, essential for precise asset
tracking within warehouses or retail spaces.
 Sensors and Actuators: Interacting with the
Physical World
Sensors: Data Collection
Sensors are the eyes and ears of IoT, gathering vital environmental and
operational data. Micro-Electro-Mechanical Systems (MEMS)
accelerometers and gyroscopes in wearables, like the Apple Watch
Series 9, provide comprehensive health tracking. Environmental
sensors, such as the Bosch BME688, meticulously monitor air quality
and CO2 levels. In industrial settings, Siemens SIMATIC sensors enable
predictive maintenance by detecting anomalies up to six months in
advance, averting costly downtime.

Actuators: Physical Actions

Actuators translate digital commands into physical actions, closing the
loop in IoT systems. Smart lighting solutions, exemplified by Philips Hue
bulbs with over 20 million units sold globally, offer dynamic control over
illumination. Robotic arms, such as the KUKA KR C4, automate complex
manufacturing processes with precision. Smart thermostats like Google
Nest contribute to sustainability and savings, cutting heating bills by
10-12% through intelligent energy management.
Cloud and Edge Computing: Processing the Data Deluge
• Cloud Computing: Centralised Power
Cloud platforms provide scalable infrastructure for processing and storing vast IoT data. AWS IoT Core handles trillions of messages monthly,
ensuring global scalability for diverse applications. Microsoft Azure IoT Hub securely manages millions of
devices. Cloud computing enables large-scale data analysis, long-term storage, and the training of complex AI models, forming the backbone
for enterprise-wide IoT solutions.
• Edge Computing: Data at the Source
Edge computing processes data closer to its origin, significantly reducing latency to less than 20ms for real-time factory automation. It
decreases bandwidth consumption by up to 50% for remote sites, making it efficient for distributed networks. Edge processing also
enhances data privacy and security by keeping sensitive information local. A prime example is smart cameras with on-device facial recognition
for rapid, secure access control.
• Edge computing processes data closer to its source, such as IoT devices or sensors, instead of relying on
centralized cloud servers. This reduces latency, enhances real-time processing, and improves data security and efficiency for
distributed networks.
 Big Data Analytics: Uncovering Insights
Big Data Analytics transforms raw IoT data into actionable
intelligence. Rolls-Royce, for instance, monitors jet engines,
processing 400,000 data points per second to predict failures
long before they occur. In retail, IoT sensors track foot traffic,
optimising store layouts and boosting sales by 7%. These
analytics identify critical patterns and trends, enabling
proactive decision-making.

Machine Learning (ML) / Artificial Intelligence (AI): Intelligent

Automation
ML and AI bring advanced capabilities to IoT. IBM Watson IoT
uses AI for anomaly detection, identifying equipment failures
before they materialise. Smart grids leverage AI to balance
energy demand, reducing peak loads by 15%. Computer Vision
automates quality control in manufacturing with 99%
accuracy, while AI-driven algorithms continually optimise
processes for efficiency and performance.
 Security and Privacy: Critical Imperatives for Trust

• Device Security
Securing IoT devices is foundational, beginning with secure boot processes and hardware roots of trust. Embedded secure
elements, such as Trusted Platform Module (TPM) chips, provide robust cryptographic key storage. Over-the-Air (OTA)
updates are crucial for patching vulnerabilities on up to 75% of devices, ensuring ongoing protection against emerging
threats.
• Network Security
Robust network security relies on strong encryption and secure protocols. TLS 1.3 ensures secure communication channels
between devices and the cloud. VPNs provide protected data transmission for sensitive applications like remote industrial
control. These measures safeguard data in transit, preventing eavesdropping and tampering.
• Data Privacy
Adherence to data privacy regulations like GDPR is paramount. Data minimisation principles ensure only essential data is
collected. Consent management platforms empower users with control over their personal data, fostering trust and
transparency. Anonymisation techniques further protect privacy while allowing for valuable data analysis.
• Threat Landscape
The IoT landscape faces significant threats, including large-scale Distributed Denial of Service (DDoS) attacks like the Mirai
botnet and pervasive data breaches. Disturbingly, up to 75% of IoT devices are vulnerable to cyberattacks due to inadequate
security measures, underscoring the urgent need for comprehensive security strategies.
 IoT Platforms and Standards: Enabling
Interoperability
IoT Platforms: Unified Management
IoT platforms provide end-to-end solutions for managing
devices, ingesting data, and deriving insights. Leading platforms
such as Google Cloud IoT, Siemens MindSphere, and Cisco IoT
offer comprehensive APIs and SDKs for seamless integration.
They also feature intuitive dashboarding and visualisation tools,
enabling users to monitor device health, analyse data, and gain
actionable intelligence from their connected ecosystems.

Standards & Protocols: Seamless Communication

Standardised protocols are essential for interoperability across
diverse IoT devices. MQTT (Message Queuing Telemetry
Transport) is a lightweight protocol ideal for constrained devices
with limited resources. CoAP (Constrained Application Protocol)
provides a web transfer protocol tailored for tiny, low-power
devices. OPC UA (Open Platform Communications Unified
Architecture) serves as a robust standard for industrial
automation, ensuring seamless data exchange in factory
environments.
 Conclusion: The Future Landscape of IoT

• Summary
The IoT revolution is driven by a convergence of critical enabling technologies: robust connectivity, intelligent sensors and
actuators, efficient computing paradigms, advanced data analytics, stringent security measures, and unified platforms and
standards. Together, these elements form the foundation of a truly connected world.
• Future Trends
❑ Digital Twins
Virtual replicas of physical assets, like GE Digital's Predix, enabling real-time simulation and optimisation.
❑ IoT-Blockchain Integration
Enhanced trust, data integrity, and transparency, particularly for supply chain management.
❑ Hyper-automation
Combining AI, ML, and Robotic Process Automation (RPA) with IoT for end-to-end operational automation.
❑ Sustainability Focus
IoT for smart energy management and waste reduction, with smart bins reducing collection costs by 30%.
Call to Action
Strategic investment in these IoT technologies is crucial for organisations aiming to achieve a significant competitive
advantage and foster continuous innovation across all sectors.