Boosting a Low-Cost Smart Home Environment with Usage and Access Control Rules

Smart Home has gained widespread attention due to its flexible integration into everyday life. Pervasive sensing technologies are used to recognize and track the activities that people perform during the day, and to allow communication and cooperation of physical objects. Usually, the available infrastructures and applications leveraging these smart environments have a critical impact on the overall cost of the Smart Home construction, require to be preferably installed during the home construction and are still not user-centric. In this paper, we propose a low cost, easy to install, user-friendly, dynamic and flexible infrastructure able to perform runtime resources management by decoupling the different levels of control rules. The basic idea relies on the usage of off-the-shelf sensors and technologies to guarantee the regular exchange of critical information, without the necessity from the user to develop accurate models for managing resources or regulating their access/usage. This allows us to simplify the continuous updating and improvement, to reduce the maintenance effort and to improve residents’ living and security. A first validation of the proposed infrastructure on a case study is also presented.

[1]  A. Schoofs,et al.  Real-Time Recognition and Profiling of Appliances through a Single Electricity Sensor , 2010, 2010 7th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON).

[2]  Antonello Calabrò,et al.  KPI Evaluation of the Business Process Execution through Event Monitoring Activity , 2015, 2015 International Conference on Enterprise Systems (ES).

[3]  James Philbin,et al.  FaceNet: A unified embedding for face recognition and clustering , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[4]  Cesare Pautasso,et al.  REST: From Research to Practice , 2011 .

[5]  Murad Khan,et al.  Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management , 2018, Sensors.

[6]  Antonello Calabrò,et al.  Leveraging Smart Environments for Runtime Resources Management , 2018, SWQD.

[7]  Fermín Galán Márquez,et al.  Handling smart environment devices, data and services at the semantic level with the FI-WARE core platform , 2014, 2014 IEEE International Conference on Big Data (Big Data).

[8]  M. Shamim Hossain,et al.  A knowledge-driven approach for activity recognition in smart homes based on activity profiling , 2020, Future Gener. Comput. Syst..

[9]  Marwan Mattar,et al.  Labeled Faces in the Wild: A Database forStudying Face Recognition in Unconstrained Environments , 2008 .

[10]  Gonçalo Marques,et al.  Monitoring Energy Consumption System to Improve Energy Efficiency , 2017, WorldCIST.

[11]  Francesca Lonetti,et al.  A Toolchain for Designing and Testing Access Control Policies , 2014, Engineering Secure Future Internet Services and Systems.

[12]  Ping Wang,et al.  Smart Home Monitoring System Based on SOC , 2017 .

[13]  Antonello Calabrò,et al.  Monitoring of Business Process Execution Based on Performance Indicators , 2015, 2015 41st Euromicro Conference on Software Engineering and Advanced Applications.

[14]  Jianqi Yu,et al.  Towards a Home Application Server , 2008, 2008 5th IEEE Consumer Communications and Networking Conference.

[15]  Mian M. Awais,et al.  EnerPlan: Smart Energy Management Planning for Home Users , 2012, ICONIP.

[16]  Omkar M. Parkhi,et al.  VGGFace2: A Dataset for Recognising Faces across Pose and Age , 2017, 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018).

[17]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.

[18]  Claudio Gennaro,et al.  Fast Image Classification for Monument Recognition , 2015, JOCCH.

[19]  Antonello Calabrò,et al.  Monitoring of Access Control Policy for Refinement and Improvements , 2018, SWQD.

[20]  Ana R. Cavalli,et al.  Multi-cloud Applications Security Monitoring , 2017, GPC.

[21]  Paolo Barsocchi,et al.  AAL Middleware Infrastructure for Green Bed Activity Monitoring , 2013, J. Sensors.

[22]  Mohammed Hassan Ahmed,et al.  Smart Home Activities: A Literature Review , 2014 .

[23]  Antonello Calabrò,et al.  GLIMPSE: a generic and flexible monitoring infrastructure , 2011, EWDC '11.

[24]  Mohan S. Kankanhalli,et al.  Tweeting Camera: A New Paradigm of Event-based Smart Sensing Device: Demo , 2016, ICDSC.

[25]  Stefano Chessa,et al.  User Movements Forecasting by Reservoir Computing Using Signal Streams Produced by Mote-Class Sensors , 2011, MOBILIGHT.

[26]  Francesca Lonetti,et al.  Testing of PolPA-based usage control systems , 2013, Software Quality Journal.

[27]  Dario Salvi,et al.  A framework for evaluating Ambient Assisted Living technologies and the experience of the universAAL project , 2015, J. Ambient Intell. Smart Environ..

[28]  Francesco Tiezzi,et al.  A Rigorous Framework for Specification, Analysis and Enforcement of Access Control Policies , 2016, IEEE Transactions on Software Engineering.

[29]  Tongliang Li,et al.  A smart home system based on embedded technology and face recognition technology , 2017, Intell. Autom. Soft Comput..

[30]  Vinton G. Cerf,et al.  Access Control and the Internet of Things , 2015, IEEE Internet Comput..

[31]  Yuxiao Hu,et al.  MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition , 2016, ECCV.

[32]  M. S. Nihaal,et al.  A Low Cost Home Automation System Using Wi-Fi Based Wireless Sensor Network Incorporating Internet of Things (IoT) , 2017, 2017 IEEE 7th International Advance Computing Conference (IACC).

[33]  Francesca Lonetti,et al.  An Automated Testing Framework of Model-Driven Tools for XACML Policy Specification , 2014, 2014 9th International Conference on the Quality of Information and Communications Technology.

[34]  Fabio Martinelli,et al.  Implementing Usage Control in Internet of Things: A Smart Home Use Case , 2017, 2017 IEEE Trustcom/BigDataSE/ICESS.

[35]  Yunpeng Zhang,et al.  Access Control in Internet of Things: A Survey , 2016, ArXiv.

[36]  Paolo Barsocchi,et al.  EvAAL, Evaluating AAL Systems through Competitive Benchmarking, the Experience of the 1st Competition , 2011, EvAAL.

[37]  Qun Li,et al.  A Survey of Fog Computing: Concepts, Applications and Issues , 2015, Mobidata@MobiHoc.

[38]  Francesca Lonetti,et al.  A toolchain for model-based design and testing of access control systems , 2015, 2015 3rd International Conference on Model-Driven Engineering and Software Development (MODELSWARD).

[39]  Stefan Poslad,et al.  Ubiquitous Computing: Basics and Vision , 2009 .

[40]  Paolo Barsocchi,et al.  EMS@CNR: An Energy monitoring sensor network infrastructure for in-building location-based services , 2014, 2014 International Conference on High Performance Computing & Simulation (HPCS).

[41]  Davide Bacciu,et al.  A cognitive robotic ecology approach to self-configuring and evolving AAL systems , 2015, Eng. Appl. Artif. Intell..

[42]  Antonello Calabrò,et al.  Towards Business Process Execution Adequacy Criteria , 2016, SWQD.

[43]  Krzysztof Czarnecki,et al.  Generative programming - methods, tools and applications , 2000 .

[44]  Kire Trivodaliev,et al.  A review of Internet of Things for smart home: Challenges and solutions , 2017 .

[45]  M. Shamim Hossain,et al.  Cyber-physical cloud-oriented multi-sensory smart home framework for elderly people: An energy efficiency perspective , 2017, J. Parallel Distributed Comput..

[46]  Teddy Surya Gunawan,et al.  Development of Face Recognition on Raspberry Pi for Security Enhancement of Smart Home System , 2017, Indonesian Journal of Electrical Engineering and Informatics (IJEEI).

[47]  Francesca Lonetti,et al.  Testing access control policies against intended access rights , 2016, SAC.

[48]  Francesca Lonetti,et al.  Assessment of Access Control Systems Using Mutation Testing , 2015, 2015 IEEE/ACM 1st International Workshop on TEchnical and LEgal aspects of data pRivacy and SEcurity.

[49]  Bhaumik Vaidya,et al.  Smart home automation with a unique door monitoring system for old age people using Python, OpenCV, Android and Raspberry pi , 2017, 2017 International Conference on Intelligent Computing and Control Systems (ICICCS).

[50]  Francesca Lonetti,et al.  Similarity testing for access control , 2015, Inf. Softw. Technol..

[51]  Antonello Calabrò,et al.  A Generative Approach for the Adaptive Monitoring of SLA in Service Choreographies , 2013, ICWE.

[52]  Stefano Chessa,et al.  Robotic Ubiquitous Cognitive Ecology for Smart Homes , 2015, Journal of Intelligent & Robotic Systems.

[53]  M. Sahani,et al.  Web-based online embedded door access control and home security system based on face recognition , 2015, 2015 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2015].

[54]  Salvatore Sessa,et al.  Development of a low-cost smart home system using wireless environmental monitoring sensors for functionally independent elderly people , 2017, 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[55]  Chang Huang,et al.  Targeting Ultimate Accuracy: Face Recognition via Deep Embedding , 2015, ArXiv.

[56]  Nelson Souto Rosa,et al.  Evaluating the Power Consumption of Wireless Sensor Network Applications Using Models , 2013, Sensors.