Smart Building (Control & Architecture) Badame , Yim

1. Smart Building(Control & Architecture)Badame, Yim

2. Topics of Presentation • Motivation • Classification • MAC • Wired • Wireless • Link • Network/Transport • Application

3. 1. Motivations

4. Residential Motivation

5. Viewing Buildings as a Closed System 70% of total electrical energy 40% of green house gases

6. Getting to know the problem

7. How much “slack”? Cyber-Physical Energy Systems: Focus on Smart Buildings by Jan Kleissl and Yuvraj Agarwal Looked into Energy of 60 buildings on University of San Diego Campus Slack on… IT: 60% Server Rooms: 50% Lights: 80% Mechanical Loads: 20%

8. 2. Classification

9. Building Automation System (BAS) Control: lighting, temperature, security, blinds, *your heart’s desire…* For both measurement and real-time control Unlike to feedback-based approach, focuses on transparently control and management electric devices in order to reduce the power consumption without explicit human controls and human noticeable degradation in QoS

10. 2. Classification by OSI 7 Layer

11. (a) MAC Layer • Wired: Energy efficient • Power line • Phone line • Ethernet • Already there! • Wireless: Installation is 20 - 80% cheaper[1]

12. MAC Wired: (Power Line Comm.) • Protocol: Home Plug 1.0 (Commercial) • Achieves Ethernet class network on-site using existing electrical wiring • Has been introduced in American market • Mitigates unpredictable noise • Splits bandwidth into many small sub channels • Masks noisy ones & others • Maintain 76 for use in U.S. market • Data rate: 1 to 14 Mbps • Nodes estimate each 5 sec. & adapt to optimal data rate

13. MAC Wired: (Power Line Comm.) • Protocol: Home Plug AV (under research/development) • By Home Plug Alliance • Goal 100 Mb/s for in home PL network • Necessary for multimedia (e.g. HDTV) • Rivals wired nw protocols (Ethernet) • Accommodates new hybrid power lines & wireless network • Simple, reliable, cost-effective • Plug-and-play

14. PLC Security • PLC is shared channel (like WiFi) • Robust security is serious issue • Encryption necessary: security vs. complexity • Rivest: 128 bit key • Home Plug: DES - 56 bit key • Intrusion & interference from adjacent subnets • e.g. Apartments - contention, degradation • Decoupling filters - isolate circuits at meter • Can also "separate" power line with router

15. Wireless MAC • Substantial costs associated with wired sensors • e.g., workload, time and cabling cost • (a) Installation of wireless is cheaper and faster  Makes it possible to increase the number of sensors  More fine-grained measurements • (b) Flexibility • Temporary infrastructure can be deployed quickly in a retrofit scenario to perform measurements during a limited time

16. MAC & Network Layer:Other Challenges of Wireless • Indoor Wireless coverage is hard • Usual Candidates: • Power ( Want to Avoid A/C for all devices) • Bandwidth • Standardizing the protocol (Must be efficient for all devices)

17. Solution?Wireless Mesh Networks! (WMNs) • 3 Components • Network gateway, Mesh router, Mesh clients • All nodes pass on information until one with internet is found • ZigBee wireless protocol

18. 4out of 5 Top vendors use it Johnson Controls, Siemens, TAC and Trane

19. Building Automation and Control NETworks • An industry standard: (ASHRAE, ANSI and ISO) • Defines 49 different types of objects • Built in categorization of them • Built in PID control loop • Compatible with IP • Levels of Priority

20. LonWorks • Combines Communication standard with “Neuron Chip” from Echelon Corp. • 2 levels of priority: 1.) Fire! 2.) Everything else

21. (1) A WSN Design Tool to Support Building Energy Management • Problem • Physical location of sensor nodes strongly influences the performance of the network • An inaccurate prediction of radio signal properties can increase the packet error rate, resulting in unplanned packet retransmission, unpredicted network performance and node lifetime (e.g., wall) • Previous Work • Only concentrate on signal coverage alone to ensure connectivity • Important to also include application specific metrics such as end to end latency or network lifetime. • Inclusion of additional metrics adds significant complexity to the design algorithm. To use centralized heuristic and search based algorithms with focus on maximizing spatial coverage and node connectivity. Not scalable. • Solution • Import Environment Description • Candidate Grid Generation • Optimization Module

22. Experiment Data

23. (2) Towards a Zero-Configuration WSN Architecture for Smart Buildings • Problem • Nowadays, the deployment of a building control system is complicated because of different communication standards • Solution • A web services-based approach to integrate resource constrained sensor and actuator nodes into IP-based networks • Capability for automatic service discovery • Implemented an API to access services on sensor nodes following the architectural style of representational state transfer

24. Design and Data

25. “Evaluation of energy-efficiency in lighting systems using sensor networks” • LightWise – WSN • Measures: • Human activity • Ambient Lighting • Artificial Lighting • Calculate smart energy saving techniques • Smart times to do certain tasks • Suggest when to turn off devices • Evaluates efficiency

26. What LightWise is thinking…

27. Results from LightWise

28. The Self-Programming Thermostat: Optimizing Setback Schedules based on Home Occupancy Patterns • Goals • Detect when users are home • Automatically develop a model • Self program the thermostat • User only needs to turn the “Bang for Buck” knob.

29. The self-programming thermostat: optimizing setback schedules based on home occupancy patterns Energy star thermostats are preset from 8:00am to 6:00pm. People don’t like the hassle of programming times People don’t have constant schedules.

30. The main idea…

31. How the Calculation is Performed

32. How the Calculation is Performed…

33. Data • Used Handwritten logs from two people over the course of a month • Kasteren • Less predictable schedule: 40% reduction in miss time • Tulum • More predictable schedule: 15% reduction in miss time

34. Application: iSense • A WSN Based Conference Room Management System • Problem • to book meeting rooms in a corporate environment • Previous Work • the status of meeting rooms is manually entered. Not reflected in real time and underutilization of resources • Measurement • a test bed of motes and analyzed the occupancy and electricity consumption data to estimate the under-utilization of conference rooms, and the wastage of electricity in the process

35. Design • Solution • Results • The utilization of the conference room is increased from 67% to 90% • Electricity saving is equivalent to 16000 full grown banyan trees in a year.

36. Application: IP-based WSN • Efficient Application Integration in IP-Based Sensor Networks • Problem • Integration of sensor networks with future energy management • Solution • IP-based sensor network where nodes communicate their information using Web services • A session-aware power-saving radio protocol • The use of the HTTP Conditional GET mechanism

37. Results

38. Application: Building Automation &Control System Difficulties • Many different systems • Control theory is needed to keep systems stable. • System modularity is difficult • Buildings are mix-use (People and Computers) • “For instance, as a caution note that a 2% decrease in the productivity of once building occupants has the same economic impact as all building maintenance and energy expenditures”[3]

39. Standard Protocols • Goal: A Dynamic network • Configuration • Sharing resources • Maintanence • Control - from anywhere, anytime • For building and CE devices administration • Custom in-house tools for building and system air conditioner • For CE devices, there are standardization activities

40. The Network WWW CLIENT SERVLET The Client clicks on the link leading to his URL requesting a service 1. Ask for the service Jini Lookup 2. Get the service proxy The services register their proxies with the lookup service, which is queried by the servlet for servicing the request from the client. 3. Interact with device DEVICES

41. Jini Connection Technology • Java centric, distributed system designed for simplicity, flexibility and federation • Members of the federation agree on basic notions of trust, administration, identification and policy • Components - Services, Infrastructure and programming model

42. Lookup Service Lookup Service Lookup’s proxy Lookup’s proxy Service Provider Service Provider

43. Lookup Service Lookup’s proxy DISCOVERY Service Provider Lookup’s proxy 1. Get Lookup’s proxy from the lookup

44. Lookup Service Lookup’s proxy Service Object JOIN Service Attributes Service Provider Lookup’s proxy 2. Register service object with lookup 1. Get Lookup’s proxy from the lookup Service Object Service Attributes

45. Lookup Service Service Object Service Attributes 1b. Query the Lookup service 2b. Gets Service Proxy Service Provider Client Service Object Service Attributes 3b. Interact with service

46. Multicast Request (Service Initiated Discovery Discoverer Lookup Service 1. Request Message (sent via UDP Multicast) IP Address - 224.0.1.85 port:4160 via UDP Multicast) IP Address - 224.0.1.85 port:4160 2. Response Message – Service Proxy sent (Sent via TCP unicast)

47. Lookup Service Lookup Service Service Object Service Attributes 1. Query the Lookup service 2. Gets Service Proxy Service Provider Client Service Object Service Attributes 3. Interact with service

48. Device Architecture Alternatives • Device with computing power, memory, full JVM • Devices with specialized JVMs - need not include security manager, code verifier, or a number of other components • Clustering of devices with a Shared Virtual Machine

49. Full Jini Capable Device Service client Service Provider Hardware Implementation Client Private Protocol Proxy JVM Network Communication via RMI protocol

50. Clustering of devices with a Jini capable proxy on the network Service client Network Proxy Client Proxy JVM Private Protocol Network Communication via RMI protocol Dev 1 Dev 2 Dev 3