Internet of Things Wireless Sensor Networks. Chenyang Lu

Transcription

1 Internet of Things Wireless Sensor Networks Chenyang Lu

2 Internet of Things Ø Convergence of q Miniaturized hardware: processor+sensors+wireless q Low-power wireless: connect millions of devices to the Internet. q Data analytics: make sense of sensor data. q Cloud computing: scalable data processing. Ø Real-time monitoring and control of physical systems q Smart *: house, healthcare, manufacturing, transportation, grid Ø We are in the Golden Age of Internet of Things! q A period in a field of endeavor when great tasks were accomplished.

3 Changing Our Lives Ø (IBM) 3

4 Revolutionizing Industry Ø Industrial Internet q (GE) Ø Process automation Ø (Emerson) Ø WirelessHART: wireless sensing/actuation in process industries Ø Real-time and reliable wireless networks Ø Dependable wireless control systems 4

5 Saving Energy Ø (DoE) Ø Communication between utility companies and household devices Ø Home-Area Network (HAN) connects meters, appliances, HVAC Ø Optimize energy efficiency while enhancing comfort 5

6 Improving Healthcare Ø Clinical deterioration in hospitalized patients q 4-17% suffer adverse events (e.g., cardiac or respiratory arrest). q Up to 70% of such events could have been prevented. q Clinical deterioration is often preceded by changes in vitals. Ø Goal: early warning of clinical deterioration à improved outcome Ø Real-time patient monitoring in general hospital wards q Current practice: collect vital signs manually every 5-10 hours q Wireless monitoring system: collects data every minute! Ø Large-scale, interdisciplinary research q Wireless sensor networks, data mining, medical informatics, clinical care 6

7 Wireless Clinical Monitoring 7

8 Potential for Detecting Clinical Events #$%& #$%&!"!" Pulmonary edema Sleep apnea #$%& Bradycardia!" O. Chipara, C. Lu, T.C. Bailey and G.-C. Roman, Reliable Clinical Monitoring using Wireless Sensor Networks: Experience in a Step-down Hospital Unit, ACM Conference on Embedded Networked Sensor Systems (SenSys),

9 Large-Scale Clinical Monitoring Scale up and integrate wireless monitoring with hospital IT infrastructure! 7 units, 4 floors, 14 months, 97 pauents R. Dor, G. Hackmann, Z. Yang, C. Lu, Y. Chen, M. Kollef and T.C. Bailey, Experiences with an End-To-End Wireless Clinical Monitoring System, Conference on Wireless Health, 2012.

10 Resilient Infrastructure Ø >26% of the nation's bridges are either structurally deficient or functionally obsolete. [ASCE 2009] Ø Wireless sensor networks for structural health monitoring q Localize damages in structures q Distributed computing for damage localization Ø Advantages over centralized approach q reduce latency by 88% q x3.4 increase in battery life under an hourly schedule G. Hackmann, W. Guo, G. Yan, C. Lu, S. Dyke, Cyber-Physical Codesign of Distributed Structural Health Monitoring with Wireless Sensor Networks, ICCPS'10. G. Hackmann, F. Sun, N. Castaneda, C. Lu and S. Dyke, A Holistic Approach to Decentralized Structural Damage Localization Using Wireless Sensor Networks, RTSS

11 Making Cities Smart Ø Ø IoT à large-scale sensing and control of physical world q Smart cities, manufacturing, grid, healthcare Ø Analytics turn sensor data into knowledge and decisions Ø Cloud provides scalable resources and services for analytics q Real-time cloud enables timely response and control Ø Example: Intelligent Transportation q Collect data from cameras and roadside detectors. q Control the traffic signals and message signs in real-time. q Sydney: controlling 3,400 signals at 1s round-trip latency. 11

12 Smart Dust Ø Processor + Sensors + Wireless Ø Miniature hardware manufactured economically in large numbers Ø Networked for monitoring and control à Internet of Things Smart Dust (UCB) 12

13 Example: Epic Core CC2420 radio LoWPAN/IPv6 2.5 x 2.5 cm RAM 10 KB ROM 48 KB TI MSP430 Clock 4/8 MHz I/O (some shared) 8 ADC (12 bit) 2 DAC (12 bit) 1 I2C 1 JTAG 1 1-Wire 2 SPI 2 UART 8 general, 8 interrupt, and 5 special pin connectors 3 V Unique hardware ID 16 MB Flash memory Typical sleep current 9μA at 3V, radio acuve ~20mA 13

14 TelosB Ø Six major I/O devices Ø Possible Concurrency q I 2 C, SPI, ADC Ø Energy Management q Turn peripherals on only when needed q Turn off otherwise 14

15 Sensor Network Testbed 15

16 Sensor Network Testbed 16

17 Grading Ø Projects 60% q Proposal and presentation: 10% q Demo I: 5% q Demo II: 5% q Final report and demo: 40% Ø Critiques 30% Ø Participation 10% 17

18 Critiques Ø 1/2 page critiques of research papers Ø Due by 10am on the class day Ø Yehan Ma in plain txt Ø Back-of-envelop notes - NOT whole essays 18

19 Project Ø Three students per team q Need permission for a bigger or smaller team. Ø Perform a system project q Develop/integrate software/hardware q Perform experiments on real systems q Write a paper q Demos 19

20 Example: Follow-Me Music 20

21 Theme: IoT Cloud Ø Hands on, system projects involving IoT cloud. Ø Develop IoT applications using Amazon cloud services q IoT, alexa, streaming, messaging, analytics Ø Experiment, measure and analyze 21

22 Steps 1. Select your favorite topic from a list 2. Form a team 3. Propose a design 4. Analyze and Implement your solution 5. Evaluate your solution 6. Demo 1, 2 and Final Demo 7. Write a technical report 22

23 Get Started Early Ø Think about topics and ideas Ø Talk to TA and me Ø Put together a team Ø A lot of work (and fun) throughout the semester! 23

24 Help Ø Office hours q Prof. Lu: Jolley 213 q TA: Haoran Li, Yehan Ma: Jolley 217 q By appointment Ø Slides, homework, announcement q 24

25 Next Class Ø Amazon Cloud Tutorial 25