📡Wireless Sensor Networks Unit 2 – Sensor Node Architecture & Components

Key Concepts

• Sensor nodes are the fundamental building blocks of wireless sensor networks (WSNs) that collect, process, and transmit data about the environment
• Sensor nodes typically consist of sensing, processing, communication, and power management components integrated into a single unit
• Sensor nodes are designed to be low-cost, low-power, and small in size to enable large-scale deployments and long-term operation
• Sensor nodes can be equipped with various sensing technologies (temperature, humidity, light, pressure) to monitor different environmental parameters
• Sensor nodes process and analyze the collected data locally using microcontrollers or microprocessors to reduce the amount of data transmitted
• Sensor nodes communicate wirelessly with other nodes and the base station using radio frequency (RF) modules operating in the ISM band (Industrial, Scientific, and Medical)
• Sensor nodes are powered by batteries or energy harvesting techniques (solar, vibration) to ensure long-term operation without frequent battery replacements
• Sensor node design involves trade-offs between energy efficiency, processing power, communication range, and cost to meet the specific application requirements

Sensor Node Components

• Sensing unit consists of sensors and analog-to-digital converters (ADCs) to measure and digitize environmental parameters
• Processing unit includes a microcontroller or microprocessor to process and analyze the collected data and control the overall operation of the sensor node
• Communication module enables wireless data transmission and reception using radio frequency (RF) transceivers operating in the ISM band (433 MHz, 915 MHz, 2.4 GHz)
• Power management unit includes batteries, voltage regulators, and power management circuits to provide stable and efficient power supply to the sensor node components
• Memory unit stores the collected data, application code, and configuration settings
  • Non-volatile memory (flash) retains data even when power is lost
  • Volatile memory (RAM) provides fast access for temporary data storage and processing
• Enclosure protects the sensor node components from environmental factors (moisture, dust, impact) and enables easy deployment and maintenance
• Optional components such as GPS modules, actuators, or external storage can be added depending on the specific application requirements

Sensing Technologies

• Temperature sensors measure the ambient temperature using thermistors, thermocouples, or integrated temperature sensors (LM35, DS18B20)
• Humidity sensors detect the amount of water vapor in the air using capacitive or resistive sensing elements (HIH-4000, DHT11)
• Light sensors measure the intensity of visible or infrared light using photodiodes, phototransistors, or integrated light sensors (TSL2561, BH1750)
• Pressure sensors measure the atmospheric pressure or the pressure of fluids using piezoresistive, capacitive, or optical sensing elements (BMP180, MPX4115A)
• Accelerometers detect the acceleration and tilt of the sensor node using MEMS (Micro-Electro-Mechanical Systems) technology (ADXL345, MPU-6050)
• Gas sensors detect the presence and concentration of specific gases (CO, CO2, NO2) using electrochemical, metal oxide, or infrared sensing principles (MQ-7, CCS811)
• Acoustic sensors capture sound waves and convert them into electrical signals using microphones or piezoelectric transducers (SPM0404UD5, ADMP401)
• Soil moisture sensors measure the water content in the soil using resistive or capacitive sensing techniques (YL-69, EC-5)

Processing Units

• Microcontrollers are low-power, low-cost, and programmable integrated circuits that combine a processor, memory, and peripherals on a single chip
  • Examples: Atmel AVR (ATmega328), PIC (PIC16F), ARM Cortex-M (STM32)
• Microprocessors are more powerful and flexible than microcontrollers but consume more power and require external memory and peripherals
  • Examples: Intel Atom, ARM Cortex-A, Raspberry Pi
• Processing units execute the sensor node firmware, which includes tasks such as sensor data acquisition, data processing, communication protocol stack, and power management
• The choice of processing unit depends on the computational requirements, power constraints, and cost considerations of the specific application
• Low-power modes and sleep scheduling techniques are used to minimize the energy consumption of the processing unit during idle periods
• The processing unit interfaces with the sensing unit through analog-to-digital converters (ADCs) and with the communication module through serial interfaces (UART, SPI, I2C)

Communication Modules

• Radio frequency (RF) transceivers enable wireless communication between sensor nodes and the base station using electromagnetic waves in the ISM band
• Low-power, short-range communication protocols such as Zigbee (IEEE 802.15.4), Bluetooth Low Energy (BLE), and LoRa are commonly used in WSNs
  • Zigbee operates in the 2.4 GHz, 915 MHz, and 868 MHz frequency bands and provides a data rate of up to 250 kbps
  • BLE operates in the 2.4 GHz frequency band and provides a data rate of up to 1 Mbps with a range of up to 100 meters
  • LoRa operates in the sub-GHz frequency bands and provides long-range communication (up to 10 km) with low data rates (0.3-50 kbps)
• The choice of communication module depends on the required communication range, data rate, power consumption, and cost of the specific application
• Antenna design and placement play a crucial role in determining the communication range and quality of the sensor node
• Communication modules implement the physical (PHY) and media access control (MAC) layers of the communication protocol stack, while the upper layers (network, transport, application) are implemented in the processing unit

Power Management

• Batteries are the primary energy source for sensor nodes, providing a finite amount of energy for long-term operation
  • Alkaline batteries have a high energy density but a limited shelf life and are not rechargeable
  • Lithium batteries have a higher energy density, longer shelf life, and are rechargeable but more expensive
• Energy harvesting techniques convert ambient energy sources into electrical energy to supplement or replace batteries
  • Solar energy harvesting uses photovoltaic cells to convert sunlight into electrical energy and is suitable for outdoor applications
  • Vibration energy harvesting uses piezoelectric or electromagnetic transducers to convert mechanical vibrations into electrical energy
  • Thermoelectric energy harvesting uses the Seebeck effect to convert temperature gradients into electrical energy
• Power management circuits include voltage regulators, DC-DC converters, and battery chargers to provide stable and efficient power supply to the sensor node components
• Low-power design techniques such as clock gating, power gating, and dynamic voltage and frequency scaling (DVFS) are used to minimize the energy consumption of the sensor node
• Duty cycling and sleep scheduling algorithms are used to periodically put the sensor node into low-power sleep modes and wake it up only when necessary for sensing, processing, or communication tasks

Design Considerations

• Energy efficiency is a critical design consideration for sensor nodes to ensure long-term operation without frequent battery replacements
  • Minimize the active time of power-hungry components such as the radio transceiver and the processing unit
  • Use low-power sensing and processing components and optimize their sampling rates and resolution
  • Implement efficient communication protocols and minimize the amount of data transmitted
• Scalability and network topology are important factors to consider when designing large-scale WSNs
  • Use multi-hop communication and clustering techniques to extend the network coverage and balance the energy consumption among nodes
  • Implement self-organizing and self-healing mechanisms to adapt to node failures and environmental changes
• Reliability and fault tolerance are essential to ensure the accurate and timely delivery of sensor data in the presence of node failures, communication errors, and environmental interference
  • Use redundancy and diversity techniques such as multiple sensors, communication paths, and data aggregation to improve the reliability of the sensor network
  • Implement error detection and correction mechanisms such as cyclic redundancy check (CRC) and forward error correction (FEC) to mitigate communication errors
• Security and privacy are critical concerns in WSNs, especially in applications involving sensitive or personal data
  • Implement encryption and authentication mechanisms to protect the confidentiality and integrity of the sensor data and prevent unauthorized access
  • Use secure key management and distribution techniques to establish trust among sensor nodes and the base station
• Cost and size constraints are important factors to consider when designing sensor nodes for large-scale deployments and resource-limited applications
  • Use commercial off-the-shelf (COTS) components and leverage economies of scale to reduce the unit cost of sensor nodes
  • Optimize the printed circuit board (PCB) layout and packaging to minimize the size and weight of the sensor node

Real-World Applications

• Environmental monitoring applications use sensor nodes to measure and track various environmental parameters such as temperature, humidity, air quality, and soil moisture
  • Examples: Precision agriculture, forest fire detection, air pollution monitoring, water quality monitoring
• Structural health monitoring applications use sensor nodes to detect and localize damage or deformation in buildings, bridges, and other infrastructure
  • Examples: Bridge health monitoring, aircraft structural monitoring, wind turbine monitoring
• Industrial monitoring applications use sensor nodes to monitor and optimize industrial processes, equipment, and assets
  • Examples: Machine condition monitoring, predictive maintenance, energy management, inventory tracking
• Healthcare monitoring applications use sensor nodes to monitor the vital signs, activity, and behavior of patients and elderly people
  • Examples: Remote patient monitoring, fall detection, medication adherence monitoring, chronic disease management
• Smart city applications use sensor nodes to monitor and manage various aspects of urban life such as traffic, parking, lighting, and waste management
  • Examples: Smart parking, smart lighting, smart waste management, traffic congestion monitoring
• Military and defense applications use sensor nodes to detect and track targets, monitor borders and perimeters, and support situational awareness and decision making
  • Examples: Battlefield surveillance, border monitoring, chemical and biological threat detection
• Wearable and mobile sensing applications use sensor nodes to monitor and analyze human activities, behaviors, and contexts using wearable devices and smartphones
  • Examples: Fitness tracking, sleep monitoring, emotion recognition, context-aware mobile applications