1 of 55

Internet of Things

Lecture 2 - Wireless Sensor Networks and Applications

2 of 55

2

1980

2010

2020

Moore

Procesare

Era informației

More than Moore

Detecție

Era interacției

Beyond Moore

Actuare

Era îmbunătățirii

Laptop

Personal Computer

Creștere exponențială

Smartphones

Tablets

Servitori Robotici

Vehicule

Autonome

Wearables

Drone

Smart

home

2040

Contopire?

3 of 55

4 of 55

5 of 55

Wireless Sensor Networks

5

6 of 55

Wireless Sensor Networks

  • Hundreds/thousands of sensors nodes
  • Monitor environment parameters
  • Gateway/base station/sink
    • Receive data from nodes
    • Send commands to nodes
  • Storage, analysis, processing in cloud

6

Lecture 2 - WSN

7 of 55

Characteristics

7

Small size

Low bandwidth (10s-100s kbps)

Star and mesh topology

Low power, battery operated

Low cost

Ad-hoc network

Unreliable wireless medium

8 of 55

Single-Hop versus Multi-Hop

  • Star topology (single-hop)
    • Sensors communicate directly with the GW
    • May need a high transmission power
    • May not be feasible to cover a wide area
    • Does not scale well
    • No routing protocol

8

Lecture 2 - WSN

Source: https://www.lprsiot.com/networks/

9 of 55

Single-Hop versus Multi-Hop

  • Mesh topology (multi-hop)
    • Sensors act as forwarders for other nodes
    • This may reduce overall the energy consumption
    • May increase coverage
    • Routing protocol

9

Lecture 2 - WSN

Source: https://www.lprsiot.com/networks/

10 of 55

Brief History

  • DARPA (US army):
    • Distributed Sensor Nets Workshop (1978)
    • Distributed Sensor Networks (DSN) program (early 1980s)
    • Sensor Information Technology (SensIT) program

  • UCLA and Rockwell Science Center
    • Wireless Integrated Network Sensors (WINS)
    • Low Power Wireless Integrated Microsensor (LWIM) (1996)

10

Lecture 2 - WSN

11 of 55

Brief History

  • UC-Berkeley
    • Smart Dust project (1999)
    • The concept of mote
  • Berkeley Wireless Research Center (BWRC)
    • PicoRadio project (2000)
  • MIT
    • μAMPS (micro-Adaptive Multidomain Power-aware Sensors) (2005)

  • Sensinode (2005) aquired by ARM in 2013

11

Lecture 2 - WSN

12 of 55

Sensor Nodes

12

13 of 55

Sensor Node Components

13

  • Low-power microcontroller
    • Limited computing power
    • Bare-metal code (Arduino)
    • OSes: NuttX, Zephyr, Contiki, RIOT, FreeRTOS, etc.

Lecture 2 - WSN

14 of 55

Sensor Node Components

14

  • Sensors
    • Scalar: temperature, light, humidity, etc.
    • Image sensors, microphones, etc.
  • Memory
    • Limited capacity

Lecture 2 - WSN

15 of 55

Sensor Node Components

15

  • Radio Transceiver
    • Low-power
    • Low data rate, limited range
  • Actuators
  • Power supply: batteries, energy harvesting

Lecture 2 - WSN

16 of 55

Network Communication

  • Low-power
  • Low-cost
  • Low data rate (Kbps-Mbps)
    • Enough for sensor data
  • Strong power consumption constraints
    • => energy limits bandwidth

16

Lecture 2 - WSN

17 of 55

Network Communication

  • IEEE 802.15.4 standard
    • Designed for WSN networks
    • Low power consumption
    • Short to medium range communication (max 100m)
    • Low data rate (250 kpbs)
    • ZigBee and 6LoWPAN are based on it
    • Widespread use in academic or commercial solutions

17

Lecture 2 - WSN

18 of 55

Network Communication

  • IEEE 802.11 standard (Wi-Fi)
    • For nodes without strict energy constraints
    • Medium power consumption
    • Widely used in commercial applications

  • Bluetooth Low Energy standard (BLE)
    • Low power consumption
    • Used in many commercial solutions
    • Nodes communicate with a mobile device

18

Lecture 2 - WSN

19 of 55

Network Communication

19

20 of 55

Network Communication

  • Protocol stacks
  • Addressing schemes (IPv4, IPv6)
  • Data transmission (802.15.4, WiFi, BLE, LoRa, LTE, 5G, etc.)
  • Transfer rate (Kbps, Mbps, Gbps)
  • Application layer (CoAP, MQTT, HTTP, etc.)

20

Lecture 2 - WSN

21 of 55

Examples of Sensor Nodes

21

MicaZ, Mica2, Mica2 Dot

UC Berkeley

Lecture 2 - WSN

Microsal

UPB

Sparrow

UPB

ESP32 Sparrow

UPB

22 of 55

IoT Research @ UPB

  • Sparrow
    • designed for energy harvesting research
  • Ultra Low-power
  • Protocol stacks and Real-Time OSes
  • Arduino compatible!
  • Days to years of battery lifetime

23 of 55

Sparrow Nodes (v3 & v4)

23

  • Low-power MCU
  • 2.4GHz transceiver
    • IEEE 802.15.4
    • 256kbps
  • Temperature, humidity, luminosity
  • 9-DOF IMU
  • 16MHz
  • 8KB RAM
  • 128KB Flash
  • 50mW, 36uW (sleep)
  • 7g, 50x30x5mm
  • ~ $10

Lecture 2 - WSN

24 of 55

ESP32 Sparrow

  • ESP32-C6 microcontroller (dual core)
  • Wi-Fi, BLE
  • Temperature, humidity, pressure, and air quality sensor (I2C)
  • 3-axis accelerometer and gyroscope (I2C)
  • Ambient light sensor (I2C)
  • 64 MB Flash memory (SPI)
  • 128x32 OLED display (I2C)

24

25 of 55

ESP32 Sparrow

  • High-quality digital microphone (I2S)
  • Neopixel RGB LED (GPIO)
  • SD card slot (SPI)
  • Low power, low cost
  • Arduino-compatible
  • NuttX, Zephyr OS

25

26 of 55

Sparrow ESP32

26

27 of 55

Applications

27

28 of 55

Deployment: Off-grid building

  • Sparrow nodes deployed in the "passive house" (energy efficient)
  • Rainwater harvesting
  • Photovoltaic panels
  • Thermal insulation
  • Energy-efficient HVAC system
  • Canadian well

28

Lecture 2 - WSN

29 of 55

Floor plan

29

Lecture 2 - WSN

30 of 55

30

31 of 55

Energy-Independent Indoor WSN

31

  • Employs energy harvesting
  • Miniature Solar Panel
  • Ultra low-power DC/DC
  • Super-capacitor storage
  • Total energy independence
  • Outdoor & indoor
  • Mounted on the wall

PV panel

with DC/DC

converter

20F Supercap

Regular Sparrow Node

Lecture 2 - WSN

32 of 55

Results

32

Lecture 2 - WSN

  • Adaptive duty-cycling => high availability
    • adjust data transmission frequency to available energy
  • Voltage between 2.2V and 3V

33 of 55

Results

33

Lecture 2 - WSN

34 of 55

Seismic Building Monitoring

34

  • Measuring and monitoring seismic activities
  • How buildings behave during a minor earthquake
  • Weekly earthquakes in Vrancea area
    • magnitude 3-4 on Richter scale

Lecture 2 - WSN

35 of 55

Seismic Building Monitoring

35

36 of 55

Platform Design

  • Sparrow nodes
  • Attached to the outside of buildings walls, on different floors
  • High-precision accelerometer
    • Monitor vibrations
  • Very high energy availability
    • Large battery
    • Autonomy of at least one year

36

Lecture 2 - WSN

37 of 55

Communication

37

Lecture 2 - WSN

38 of 55

Experimental Setup

  • Seismic shake table
    • slide and vibrate in two axes
    • simulates the resistance structure of a building using a metallic structure
  • At each level - a sensor node

38

Lecture 2 - WSN

39 of 55

Results

  • Seismic waves on each floor
  • Behavior is completely different depending on the distance from the base

39

Lecture 2 - WSN

40 of 55

Microsal – Salivary Pacemaker

  • Neuro-electrostimulator for salivary glands
  • Treatment of xerostomia
  • Level of salivary pH and humidity in the oral cavity
  • Stimulate the salivary glands to produce more saliva
  • Miniaturized dental implant

40

Lecture 2 - WSN

41 of 55

Microsal – Salivary Pacemaker

  • Connectivity to a tablet through BLE
    • Receive and visualize collected data
    • Set parameters for neural stimulation
  • Data is sent and stored in Cloud

41

Lecture 2 - WSN

42 of 55

Microsal – Salivary Pacemaker

42

Lecture 2 - WSN

43 of 55

Microsal – Salivary Pacemaker

43

Lecture 2 - WSN

44 of 55

CityAirQ - Pollution Tracking System

  • Wearable air quality monitor
  • CO2, NOx, PM1, PM2.5, PM10

44

45 of 55

CityAirQ - Pollution Tracking System

45

46 of 55

CityAirQ - Pollution Tracking System

46

47 of 55

CityAirQ - Pollution Tracking System

47

48 of 55

CityAirQ - Pollution Tracking System

48

49 of 55

CityAirQ - Pollution Tracking System

49

50 of 55

CityAirQ - Pollution Tracking System

50

51 of 55

CityAirQ - Pollution Tracking System

  • Latest device version
  • Wearable

51

52 of 55

TinySense

  • Can you power a battery-less device with only solar energy?
  • Solar panels, supercapacitors
  • Sensors: BME 280 (temperature, humidity, pressure), IIS2MDC (magnetic)

53 of 55

UpdateMate

53

  • E-ink tablet
  • Display surface for sensor data and other information
  • Low-power
  • Open source

54 of 55

Hacktor Watch

54

  • Open-source
  • Open-hardware
  • Based on ESP32
    • dual-core
    • low-power
  • NuttX OS
  • Arduino
  • AI/ML capabilities

55 of 55

Keywords

  • Wireless Sensor Networks
  • Sensor node
  • Single-hop
  • Multi-hop
  • Sparrow
  • Sparrow ESP32
  • CityAirQ
  • TinySense
  • UpdateMate
  • Hacktor Watch

55

Lecture 2 - WSN