Smart Grid and IoT

Smart Grid

• The goal is to provide energy to a growing population with fewer resources.
• The aims are to reduce losses, improve efficiency, and support renewable energy sources.
• There is a shift from centralized to distributed grid topology.

Role of IoT

• This enables automation, monitoring, and optimization.
• There is support for smart in-home/building devices for user monitoring and control.
• Sensors help manage occupancy and lighting, adjusting loads during off-peak hours.

Smart Meters

• They are a key component for tracking real-time energy consumption.
• They allow for self-healing grids and smarter decision-making.
• They enable two-way communication and remote management such as dynamic pricing, and security updates.

Communication Layers

• HAN (Home Area Network) connects appliances, smart meters, EVs, and renewables inside homes/buildings.
• NAN (Neighborhood/Field Area Network) connects multiple HANs, and relays data to WAN.
• WAN (Wide Area Network) is the backbone for data exchange between control centers and field equipment.

Connectivity Technologies

• They vary by region such as RF mesh in the U.S., or PLC in France/Spain.
• There is no universal solution and requires a mix of wired and wireless technologies.

Smart Meter Requirements

• Smart meters report usage to utilities and display info to users.
• They help users manage energy use and lower bills.

Four Subsystems Enhanced by IoT

• Power Generation: monitoring emissions, managing distributed/renewable sources.
• Power Transmission: monitoring lines, substations, and towers.
• Power Distribution: automation, operations, and equipment management.
• Power Utilization: smart homes, EVs, meter reading, load control, and energy efficiency.

IoT-Supported Smart Grid Architecture

• The objective is to enhance energy efficiency in buildings, which account for a major share of global energy use (71% in the U.S.).

Key Technologies

• IoT, smartphones, cloud computing, and location-based automation.

Architecture Components

• Multi-source energy saving policies operate at different levels such as building, department, lab, and room.
• Monitoring and control happen via mobile devices such as smartphones/PCs.
• Location-based automatic control uses smartphone GPS and movement data.
• A cloud computing platform is used for data storage, analysis, and system configuration.

Smartphone Capabilities

• Equipped with Wi-Fi, 3G/4G, Bluetooth, and GPS for energy system interaction.
• Allow real-time user interaction with policy servers to adjust energy use dynamically.

Location-Based Control Example

• As a user moves toward the office, systems trigger heating/cooling at the office and reduce energy use at home.

Cloud Platform Role

• Stores and analyzes energy consumption data.
• Hosts a user-friendly web interface for remote energy management.
• Provides secure, reliable communication and system configurability.

Healthcare Smart Systems

• There is an aging population that increases the need for accessible, non-intrusive healthcare solutions.

IoT in Healthcare Enables

• Remote patient care at home or anywhere globally.
• Use of wearable sensors for proactive, preventive care.
• Reduced hospital readmissions through continuous monitoring.

Key Applications

• Patient care and monitoring.
• Medical asset tracking such as supplies, and medicine.
• Equipment maintenance using predictive diagnostics.
• Usage tracking of medical devices and facilities such as beds, temperature, and hygiene stations.

Benefits

• Enhances patient quality of life without drastic lifestyle changes.
• Improves efficiency for medical staff and healthcare operations.
• Enables creation of participatory, personalized medical knowledge.

System Overview

• IoT creates a network of connected resources for healthcare tasks like diagnosis, monitoring, and even remote surgeries.

Roche Diagnostics

• Roche’s IVD Solutions aid clinicians in disease detection, diagnosis, and patient monitoring.
• They use advanced technologies such as immunoassays, urinalysis, and point-of-care testing.

IoT Adoption Goals

• Remote monitoring and management of IVD devices across wide regions such as China.
• Predictive maintenance helps to avoid downtime by analyzing operational data.
• Personalized solution recommendations happen via analysis of device usage data.

IoT Implementation

• Cloud solutions were evaluated based on architecture maturity, development speed, and security.
• Microsoft Azure IoT solution accelerators and IoT Hub were selected.

Key Benefits Gained

• Real-time operational data collection and remote device health assessment.
• Early issue detection and alarm-based support dispatch.
• Improved asset monitoring, supply management, and usage optimization.
• Enhanced data visualization and analytics improves decision-making.
• A foundation was laid for future predictive maintenance capabilities.

365mc Health Provider

• 365mc is a Korean leader in dieting and liposuction treatments.
• AI and IoT were combined to improve liposuction precision and patient outcomes.

M.A.I.L. System (Motion capture and AI-assisted Liposuction)

• Uses a sensor-equipped cannula to capture surgeon hand movement data in real-time.
• Motion sensors (accelerometer + gyroscope) track 12,000–20,000 movements per surgery.
• Generates up to 180,000 data entries per procedure for analysis.

Goals and Benefits

• Increase precision and consistency in fat extraction.
• Prevent surgical errors such as muscle damage, uneven fat removal, and skin necrosis.
• Shifts patients from relying solely on surgeon skill to data-driven assistance.
• Immediate detection of abnormal cannula movement allows for faster response to issues.

Technology Used

• Microsoft Azure IoT collects data and real-time monitoring.
• Azure Machine Learning analyzes large datasets, 2 billion movements over 2 years.

Future Plans

• AI will alert surgeons showing unusual behavior for health checks.
• Data use will expand to personalized weight-loss tracking tools via wearables.
• Surgery safety and accuracy will continue to be enhanced through digital technologies.

Core Insight

• AI, sensors, and data analysis complement human skill, overcoming sensory limitations and improving surgical outcomes.

Smart Hospital System (SHS)

• There is real-time collection and monitoring of environmental and patient physiological data.
• Healthcare staff are alerted in case of emergencies such as falls, and heartbeat issues.

Key Components

• RFID-enhanced WSN (HSN): Includes 6LoWPAN nodes (6LBR, 6LR, 6LRR, HT).
• Tracks patients, staff, and equipment using RFID tags.
• The HT node worn by patients collects vital signs like heartbeat and motion.

IoT Smart Gateway

• Bridges the HSN network to the Internet via LAN.
• Hosts the monitoring application.

User Interfaces

• Web and mobile apps are used for local/remote data access and system management.

Data Flow & Access

• Sensor data is transmitted to the gateway and stored in a control database (DB).
• Doctors access real-time and historical data via a REST-based web interface or Medical App.
• The Medical App allows reading/updating patient records via RFID.

Emergency Handling

• The HT node uses IEEE 802.15.4 radio for urgent alerts.
• Energy-efficient strategy: RFID for routine ops, radio for emergencies only.

Security Features

• User authentication and privileged access control.
• Encrypted communication via VPN channels for secure remote access.
• Secure mobile app configuration for data integrity and privacy.

Benefits

• Real-time health monitoring, enhanced emergency response.
• Accurate patient tracking and medical history logging.
• Energy-efficient and scalable healthcare infrastructure.