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Internet of Things CSE 521S Wireless Sensor Networks Internet of Things CSE 521S Wireless Sensor Networks Chenyang Lu Internet ofThings Ø Convergence of q Miniaturized devices: processor+sensors+radio, embedded OS. q Low-power wireless: connect millions of devices to the Internet. q Data analytics: make sense of sensor data. q Cloud and edge computing: scalable real-time 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.” 2 Revolutionizing Industry Ø Industrial control systems are embracing new technologies q Edge computing: on-premise computing resources q Wireless networks: flexibility and easy deployment Ø https://www.youtube.com/watch?v=LNMmmjz5nCo (Emerson) tank level temperature valve vibration motor pressure Controller https://www.automation.com 3 Saving Energy Ø https://www.youtube.com/watch?v=JwRTpWZReJk (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 4 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 5 Wireless Clinical Monitoring Rapid Response 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 (WH'12), October 2012. 6 Potential for Detecting 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), 2010. 7 Large-Scale Clinical Monitoring Scale up and integrate wireless monitoring with hospital IT infrastructure! 7 units, 4 floors, 14 months, 97 patients 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. 8 Smartwatch as a Healthcare Tool Continuous, Open, programmable passive platform measurements onboard analytics activity, heart rate, sleep,stress… Tw o -way communication ecological momentary assessments “I believe, if you zoom out into the future, and you look back, and you ask the question, 'What was Apple's greatest contribution to mankind?', it will be about health.” --Tim Cook 9 Predict Readmissions with Fitbit Ø Hospital readmission rate is high for heart failure patients. q ~25% patients readmitted within 30 days Ø Predict deterioration (readmission+death) after discharge q Fitbit provides continuous monitoring of outpatients q Just-in-time intervention à better outcome and lower cost D. Li, J. Vaidya, M. Wang, B. Bush, C. Lu, M. Kollef and T. Bailey, Feasibility Study of Monitoring Deterioration of Outpatients Using Multi-modal Data Collected by Wearables, ACM Transactions on Computing for Healthcare, 1(1), Article 5, 2020.. 10 Make Cities Smart Ø Sydney Coordinated Adaptive Traffic System (SCATS) Ø Controlling 3,400 signals at 1s round-trip latency. Ø Cloud collects data from cameras and roadside detectors. Ø Control the traffic signals and message signs in real-time. Source: https://www.scats.nsw.gov.au 11 Devices 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 Wireless Technologies Ø Wireless Personal Area Networks (WPAN) q Bluetooth Low Energy (BLE) q IEEE 802.15.4 radio (PHY): Thread, Zigbee, WirelessHART Ø Wireless Local Area Networks (WLAN) q WiFi Ø Wireless Wide Area Networks (WWAN) q Cellular: NB-IoT q Low Power Wide Area (LPWA): LoRa, SigFox Ø Choice of wireless technology depends on range, data rate, latency, power… Source & Copyright 13 Digitize or Die IoT book Jolley Te s t b e d 14 Amazon FreeRTOS + AWS https://aws.amazon.com/freertos Chenyang Lu 15 What are you going to learn? Ø Full IoT Stack q Miniaturized devices: processor+sensors+radio, embedded OS. q Low-power wireless: connect millions of devices to the Internet. q Data analytics: make sense of sensor data. q Cloud and edge computing: scalable and real-time data processing. Ø Cutting-edge research papers Ø Hands-on, integrated IoT system project 16 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 Critiques Ø 1/2 page critiques of research papers Ø Due by 10am on the class day Ø Back-of-envelop notes - NOT whole essays Ø Critique requirement 18 Project Ø Three students per team q Need permission for a bigger or smaller team. Ø Perform a full-stack, system project q Develop/integrate software/hardware q Perform experiments on real systems q Write a paper q Demos 19 Example: Follow-Me Music 20 Minimum Viable Product (MVP) Ø Build full-stack IoT applications q Device q Wireless q Cloud q Analytics Ø Leverage cloud services q AWS IoT, Alexa, streaming, messaging, analytics… Ø Experiment, measure and analyze 21 Steps 1. Find your favorite topic 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 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 Logistics Ø Guidelines and slides are on the class homepage. q http://www.cse.wustl.edu/~lu/cse521s/ Ø Lectures will be delivered live on Zoom (TBD). Ø Video recordings will be available after class. Ø Discussions and communication will be on Piazza. q Post on Icebreaker (think about project ideas) q Search for teammate Ø Attend class in person for project proposals and demos. 24 Help Ø Prof. Lu <[email protected]> Ø Projects: Hanyang (Eric) Liu <[email protected]> Ø Critiques: Jingwen Zhang <[email protected]> Ø Make appointment for Zoom meetings. Ø Post on Piazza for Q&A. 25 Next Class Ø Amazon Cloud Tutorial Ø Prerecorded lecture 26.
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