Design Automation for Smart Building Systems

Smart buildings today are aimed at providing safe, healthy, comfortable, affordable, and beautiful spaces in a carbon and energy-efficient way. They are emerging as complex cyber–physical systems with humans in the loop. Cost, the need to cope with increasing functional complexity, flexibility, fragmentation of the supply chain, and time-to-market pressure are rendering the traditional heuristic and ad hoc design paradigms inefficient and insufficient for the future. In this paper, we present a platform-based methodology for smart building design. Platform-based design (PBD) promotes the reuse of hardware and software on shared infrastructures, enables rapid prototyping of applications, and involves extensive exploration of the design space to optimize design performance. In this paper, we identify, abstract, and formalize components of smart buildings, and present a design flow that maps high-level specifications of desired building applications to their physical implementations under the PBD framework. A case study on the design of on-demand heating, ventilation, and air conditioning (HVAC) systems is presented to demonstrate the use of PBD.

[1]  Peter L. Bartlett,et al.  Rademacher and Gaussian Complexities: Risk Bounds and Structural Results , 2003, J. Mach. Learn. Res..

[2]  Andrew Peter Wallace McCarthy.  E DITOR ’ S C OMMENTS Diversity of Design Science Research , 2022 .

[3]  Davide Bresolin,et al.  A Platform-Based Design Methodology With Contracts and Related Tools for the Design of Cyber-Physical Systems , 2015, Proceedings of the IEEE.

[4]  Edmond Cretu,et al.  Smart sensor network for smart buildings , 2016, 2016 IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON).

[5]  Anibal T. de Almeida,et al.  Sensor-based demand-controlled ventilation: a review , 1998 .

[6]  Miguel Á. Carreira-Perpiñán,et al.  Occupancy Modeling and Prediction for Building Energy Management , 2014, ACM Trans. Sens. Networks.

[7]  Jack Chin Pang Cheng,et al.  Estimation of the building energy use intensity in the urban scale by integrating GIS and big data technology , 2016 .

[8]  Alberto L. Sangiovanni-Vincentelli,et al.  A Contract-Based Methodology for Aircraft Electric Power System Design , 2014, IEEE Access.

[9]  Ming Jin,et al.  MapSentinel: Can the Knowledge of Space Use Improve Indoor Tracking Further? , 2016, Sensors.

[10]  José Domingo Álvarez,et al.  Optimizing building comfort temperature regulation via model predictive control , 2013 .

[11]  Alberto L. Sangiovanni-Vincentelli,et al.  Development of Building Automation and Control Systems , 2012, IEEE Design & Test of Computers.

[12]  Thierry S. Nouidui,et al.  Modelica Buildings library , 2014 .

[13]  David E. Culler,et al.  Enabling advanced environmental conditioning with a building application stack , 2013, 2013 International Green Computing Conference Proceedings.

[14]  Andreas Junghanns,et al.  Functional Mockup Interface 2.0: The Standard for Tool independent Exchange of Simulation Models , 2012 .

[15]  Alberto L. Sangiovanni-Vincentelli,et al.  Benefits and challenges for platform-based design , 2004, Proceedings. 41st Design Automation Conference, 2004..

[16]  Ming Jin,et al.  A Robust Utility Learning Framework via Inverse Optimization , 2017, IEEE Transactions on Control Systems Technology.

[17]  Yuebin Yu,et al.  A review of fault detection and diagnosis methodologies on air-handling units , 2014 .

[18]  Edward A. Lee,et al.  System-Level Types for Component-Based Design , 2001, EMSOFT.

[19]  Daniel E. Fisher,et al.  EnergyPlus: creating a new-generation building energy simulation program , 2001 .

[20]  Ákos Horváth,et al.  Multi-objective optimization in rule-based design space exploration , 2014, ASE.

[21]  Alvise Bonivento,et al.  Platform based design for wireless sensor networks , 2005, 2nd International Workshop Networking with Ultra Wide Band and Workshop on Ultra Wide Band for Sensor Networks, 2005. Networking with UWB 2005..

[22]  Steven X. Ding,et al.  A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches , 2015, IEEE Transactions on Industrial Electronics.

[23]  M Frontczak,et al.  Quantitative relationships between occupant satisfaction and satisfaction aspects of indoor environmental quality and building design. , 2012, Indoor air.

[24]  Alberto L. Sangiovanni-Vincentelli,et al.  Optimized design of a Human Intranet network , 2017, 2017 54th ACM/EDAC/IEEE Design Automation Conference (DAC).

[25]  Diane J. Cook,et al.  How smart are our environments? An updated look at the state of the art , 2007, Pervasive Mob. Comput..

[26]  Yao-Jung Wen,et al.  Wireless networked lighting systems for optimizing energy savings and user satisfaction , 2008, 2008 IEEE Wireless Hive Networks Conference.

[27]  Francesco Borrelli,et al.  Bilinear Model Predictive Control of a HVAC System Using Sequential Quadratic Programming , 2011 .

[28]  Xuening Sun,et al.  Methodology for the Design of Analog Integrated Interfaces Using Contracts , 2012, IEEE Sensors Journal.

[29]  Mohammad Esmalifalak,et al.  A data mining approach for fault diagnosis: An application of anomaly detection algorithm , 2014 .

[30]  Michael R. Brambley,et al.  Review Article: Methods for Fault Detection, Diagnostics, and Prognostics for Building Systems—A Review, Part II , 2005 .

[31]  Christian Ghiaus,et al.  Optimal temperature control of intermittently heated buildings using Model Predictive Control: Part , 2012 .

[32]  D. Kolokotsa,et al.  Comparison of the performance of fuzzy controllers for the management of the indoor environment , 2003 .

[33]  Alberto L. Sangiovanni-Vincentelli,et al.  Quo Vadis, SLD? Reasoning About the Trends and Challenges of System Level Design , 2007, Proceedings of the IEEE.

[34]  David E. Culler,et al.  XBOS: An Extensible Building Operating System , 2015 .

[35]  Michael Wetter,et al.  Modelica-based modelling and simulation to support research and development in building energy and control systems , 2009 .

[36]  Xuan Luo,et al.  Performance evaluation of an agent-based occupancy simulation model , 2017 .

[37]  Prabir Barooah,et al.  Occupancy-based zone-climate control for energy-efficient buildings: Complexity vs. performance , 2013 .

[38]  Fernanda Leite,et al.  Integrating probabilistic methods for describing occupant presence with building energy simulation models , 2014 .

[39]  Alberto L. Sangiovanni-Vincentelli,et al.  ArchEx: An extensible framework for the exploration of cyber-physical system architectures , 2017, 2017 54th ACM/EDAC/IEEE Design Automation Conference (DAC).

[40]  Building-in-Briefcase (BiB) , 2014, ArXiv.

[41]  Luca P. Carloni,et al.  Supervised design space exploration by compositional approximation of Pareto sets , 2011, 2011 48th ACM/EDAC/IEEE Design Automation Conference (DAC).

[42]  Hui Zhang,et al.  Energy-efficient comfort with a heated/cooled chair: Results from human subject tests , 2015 .

[43]  Alberto L. Sangiovanni-Vincentelli,et al.  Platform-Based Design for Embedded Systems , 2005, Embedded Systems Handbook.

[44]  M. Sgroi,et al.  The art and science of integrated systems design , 2002, Proceedings of the 28th European Solid-State Circuits Conference.

[45]  Gabor Karsai,et al.  Model-Integrated Computing , 1997, Computer.

[46]  Roberto Passerone,et al.  Optimized Selection of Wireless Network Topologies and Components via Efficient Pruning of Feasible Paths , 2018, 2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC).

[47]  Alberto L. Sangiovanni-Vincentelli,et al.  A mixed discrete-continuous optimization scheme for Cyber-Physical System architecture exploration , 2015, 2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD).

[48]  Ming Jin,et al.  Sensing by Proxy : Occupancy Detection Based on Indoor CO 2 Concentration , 2015 .

[49]  Kurt Keutzer,et al.  The Concurrency Challenge , 2008, IEEE Design & Test of Computers.

[50]  Stefano Schiavon,et al.  Occupant satisfaction in LEED and non-LEED certified buildings , 2013 .

[51]  K. Keutzer,et al.  System-level design: orthogonalization of concerns andplatform-based design , 2000, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[52]  Ioannis C. Konstantakopoulos,et al.  Smart building energy efficiency via social game: a robust utility learning framework for closing–the–loop , 2016, 2016 1st International Workshop on Science of Smart City Operations and Platforms Engineering (SCOPE) in partnership with Global City Teams Challenge (GCTC) (SCOPE - GCTC).

[53]  W. H. Engelmann,et al.  The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants , 2001, Journal of Exposure Analysis and Environmental Epidemiology.

[54]  Alberto L. Sangiovanni-Vincentelli,et al.  Moving From Federated to Integrated Architectures in Automotive: The Role of Standards, Methods and Tools , 2010, Proceedings of the IEEE.

[55]  Hao Jiang,et al.  A Robust Indoor Positioning System Based on the Procrustes Analysis and Weighted Extreme Learning Machine , 2016, IEEE Transactions on Wireless Communications.

[56]  Alberto L. Sangiovanni-Vincentelli,et al.  Platform-Based Design and Software Design Methodology for Embedded Systems , 2001, IEEE Des. Test Comput..

[57]  Thierry S. Nouidui,et al.  Functional mock-up unit for co-simulation import in EnergyPlus , 2014 .

[58]  Stefano Schiavon,et al.  Room air stratification in combined chilled ceiling and displacement ventilation systems , 2011 .

[59]  Ming Jin,et al.  Longitudinal Assessment of Thermal and Perceived Air Quality Acceptability in Relation to Temperature, Humidity, and CO2 Exposure in Singapore , 2017 .

[60]  Alberto L. Sangiovanni-Vincentelli,et al.  System design: traditional concepts and new paradigms , 1999, Proceedings 1999 IEEE International Conference on Computer Design: VLSI in Computers and Processors (Cat. No.99CB37040).

[61]  Alberto L. Sangiovanni-Vincentelli,et al.  Optimized selection of reliable and cost-effective cyber-physical system architectures , 2015, 2015 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[62]  Costas J. Spanos,et al.  Learning Optimization Friendly Comfort Model for HVAC Model Predictive Control , 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).

[63]  Zhiwei Gao,et al.  From Model, Signal to Knowledge: A Data-Driven Perspective of Fault Detection and Diagnosis , 2013, IEEE Transactions on Industrial Informatics.

[64]  S Schiavon,et al.  Thermal comfort, perceived air quality, and cognitive performance when personally controlled air movement is used by tropically acclimatized persons , 2017, Indoor air.