Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
143 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
46 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Automation of Smart Homes with Multiple Rule Sources (2401.02451v1)

Published 3 Jan 2024 in cs.CR and cs.LG

Abstract: Using rules for home automation presents several challenges, especially when considering multiple stakeholders in addition to residents, such as homeowners, local authorities, energy suppliers, and system providers, who will wish to contribute rules to safeguard their interests. Managing rules from various sources requires a structured procedure, a relevant policy, and a designated authority to ensure authorized and correct contributions and address potential conflicts. In addition, the smart home rule language needs to express conditions and decisions at a high level of abstraction without specifying implementation details such as interfaces, access protocols, and room layout. Decoupling high-level decisions from these details supports the transferability and adaptability of rules to similar homes. This separation also has important implications for structuring the smart home system and the security architecture. Our proposed approach and system implementation introduce a rule management process, a rule administrator, and a domain-specific rule language to address these challenges. In addition, the system provides a learning process that observes residents, detects behavior patterns, and derives rules which are then presented as recommendations to the system.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (34)
  1. Multi-objective scheduling of iot-enabled smart homes for energy management based on arithmetic optimization algorithm: A node-red and nodemcu module-based technique. Knowl. Based Syst., 247:108762.
  2. Iot elements, layered architectures and security issues: A comprehensive survey. Sensors, 18(9):2796.
  3. Towards automatic conflict detection in home and building automation systems. Pervasive Mob. Comput., 12:37–57.
  4. Low cost house automation system based on arduino microcontroller. In IEEE Industry Applications Society Annual Meeting, IAS 2021, Vancouver, BC, Canada, October 10-14, 2021, pages 1–6. IEEE.
  5. Learning phrase representations using RNN encoder-decoder for statistical machine translation. In Moschitti, A., Pang, B., and Daelemans, W., editors, Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014, October 25-29, 2014, Doha, Qatar, A meeting of SIGDAT, a Special Interest Group of the ACL, pages 1724–1734. ACL.
  6. Personalization of context-dependent applications through trigger-action rules. ACM Trans. Comput. Hum. Interact., 24(2):14:1–14:33.
  7. Smart home automation system using arduino microcontrollers. In IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR 2020, Cluj-Napoca, Romania, May 21-23, 2020, pages 1–7. IEEE.
  8. Heimdall: Mitigating the internet of insecure things. IEEE Internet Things J., 4(4):968–978.
  9. Session-based recommendations with recurrent neural networks. In Bengio, Y. and LeCun, Y., editors, 4th International Conference on Learning Representations, ICLR 2016, San Juan, Puerto Rico, May 2-4, 2016, Conference Track Proceedings.
  10. A survey on conflict detection in iot-based smart homes. CoRR, abs/2310.04447.
  11. Integrated management of energy, wellbeing and health in the next generation of smart homes. Sensors, 19(3):481.
  12. Matrix factorization techniques for recommender systems. Computer, 42(8):30–37.
  13. Context aware recommendation systems: A review of the state of the art techniques. Comput. Sci. Rev., 37:100255.
  14. Context-aware sequential recommendation. In Bonchi, F., Domingo-Ferrer, J., Baeza-Yates, R., Zhou, Z., and Wu, X., editors, IEEE 16th International Conference on Data Mining, ICDM 2016, December 12-15, 2016, Barcelona, Spain, pages 1053–1058. IEEE Computer Society.
  15. A new layered architecture for future big data-driven smart homes. IEEE Access, 7:19002–19012.
  16. Iot security framework for smart cyber infrastructures. In Elnikety, S., Lewis, P. R., and Müller-Schloer, C., editors, 2016 IEEE 1st International Workshops on Foundations and Applications of Self* Systems (FAS*W), Augsburg, Germany, September 12-16, 2016, pages 242–247. IEEE.
  17. Iotguard: Scalable and agile safeguards for internet of things. In Brand, J., Valenti, M. C., Akinpelu, A., Doshi, B. T., and Gorsic, B. L., editors, 2016 IEEE Military Communications Conference, MILCOM 2016, Baltimore, MD, USA, November 1-3, 2016, pages 61–66. IEEE.
  18. Intelligent multi-agent collaboration model for smart home iot security. In 2018 IEEE International Congress on Internet of Things, ICIOT 2018, San Francisco, CA, USA, July 2-7, 2018, pages 65–71. IEEE Computer Society.
  19. Context-aware sequential recommendations withstacked recurrent neural networks. In Liu, L., White, R. W., Mantrach, A., Silvestri, F., McAuley, J. J., Baeza-Yates, R., and Zia, L., editors, The World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13-17, 2019, pages 3172–3178. ACM.
  20. Sequential recommendation with self-attentive multi-adversarial network. In Huang, J. X., Chang, Y., Cheng, X., Kamps, J., Murdock, V., Wen, J., and Liu, Y., editors, Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, SIGIR 2020, Virtual Event, China, July 25-30, 2020, pages 89–98. ACM.
  21. Factorizing personalized markov chains for next-basket recommendation. In Rappa, M., Jones, P., Freire, J., and Chakrabarti, S., editors, Proceedings of the 19th International Conference on World Wide Web, WWW 2010, Raleigh, North Carolina, USA, April 26-30, 2010, pages 811–820. ACM.
  22. Fast context-aware recommendations with factorization machines. In Ma, W., Nie, J., Baeza-Yates, R., Chua, T., and Croft, W. B., editors, Proceeding of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2011, Beijing, China, July 25-29, 2011, pages 635–644. ACM.
  23. Towards in-network security for smart homes. In Doerr, S., Fischer, M., Schrittwieser, S., and Herrmann, D., editors, Proceedings of the 13th International Conference on Availability, Reliability and Security, ARES 2018, Hamburg, Germany, August 27-30, 2018, pages 18:1–18:8. ACM.
  24. Raspimonitor: A raspberry pi based smart home monitoring system. In 3rd International Conference on Next Generation Computing Applications, NextComp 2022, Flic-en-Flac, Mauritius, October 6-8, 2022, pages 1–6. IEEE.
  25. Sh-blockcc: A secure and efficient internet of things smart home architecture based on cloud computing and blockchain technology. Int. J. Distributed Sens. Networks, 15(4).
  26. Bert4rec: Sequential recommendation with bidirectional encoder representations from transformer. In Zhu, W., Tao, D., Cheng, X., Cui, P., Rundensteiner, E. A., Carmel, D., He, Q., and Yu, J. X., editors, Proceedings of the 28th ACM International Conference on Information and Knowledge Management, CIKM 2019, Beijing, China, November 3-7, 2019, pages 1441–1450. ACM.
  27. Personalized top-n sequential recommendation via convolutional sequence embedding. In Chang, Y., Zhai, C., Liu, Y., and Maarek, Y., editors, Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, WSDM 2018, Marina Del Rey, CA, USA, February 5-9, 2018, pages 565–573. ACM.
  28. Practical trigger-action programming in the smart home. In Jones, M., Palanque, P. A., Schmidt, A., and Grossman, T., editors, CHI Conference on Human Factors in Computing Systems, CHI’14, Toronto, ON, Canada - April 26 - May 01, 2014, pages 803–812. ACM.
  29. Sequential recommender systems: Challenges, progress and prospects. In Kraus, S., editor, Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019, pages 6332–6338. ijcai.org.
  30. Attentional factorization machines: Learning the weight of feature interactions via attention networks. In Sierra, C., editor, Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, August 19-25, 2017, pages 3119–3125. ijcai.org.
  31. CFM: convolutional factorization machines for context-aware recommendation. In Kraus, S., editor, Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019, pages 3926–3932. ijcai.org.
  32. Toward software defined smart home. IEEE Commun. Mag., 54(5):116–122.
  33. Transrec++: Translation-based sequential recommendation with heterogeneous feedback. Frontiers Comput. Sci., 16(2):162615.
  34. Trace2tap: Synthesizing trigger-action programs from traces of behavior. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 4(3):104:1–104:26.

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now