{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T12:10:34Z","timestamp":1756383034490,"version":"3.41.0"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030780944"},{"type":"electronic","value":"9783030780951"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-78095-1_37","type":"book-chapter","created":{"date-parts":[[2021,7,2]],"date-time":"2021-07-02T23:20:19Z","timestamp":1625268019000},"page":"507-518","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Framework for Controlling KNX Devices Based on Gestures"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6925-8323","authenticated-orcid":false,"given":"Jedid","family":"Santos","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8416-2343","authenticated-orcid":false,"given":"Ivo","family":"Martins","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3562-6025","authenticated-orcid":false,"given":"Jo\u00e3o M. F.","family":"Rodrigues","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,7,3]]},"reference":[{"issue":"1\u20132","key":"37_CR1","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1023\/A:1011144232235","volume":"11","author":"C Stephanidis","year":"2001","unstructured":"Stephanidis, C.: Adaptive techniques for universal access. User Model. User-adap. Interact. 11(1\u20132), 159\u2013179 (2001)","journal-title":"User Model. User-adap. Interact."},{"key":"37_CR2","doi-asserted-by":"publisher","unstructured":"Rodrigues, J.M.F., et al.: Adaptive card design UI implementation for an augmented reality museum application. In: Antona, M., Stephanidis, C. (eds.) Universal Access in Human-Computer Interaction 2017, Part I, LNCS 10277, pp. 433\u2013443 (2017). https:\/\/doi.org\/10.1007\/978-3-319-58706-6_35","DOI":"10.1007\/978-3-319-58706-6_35"},{"key":"37_CR3","doi-asserted-by":"crossref","unstructured":"Johnston, V., Black, M., Wallace, J., Mulvenna, M., Bond, R.: A framework for the development of a dynamic adaptive intelligent user interface to enhance the user experience. In: Proceedings of the 31st European Conference on Cognitive Ergonomics, pp. 32\u201335 (2019)","DOI":"10.1145\/3335082.3335125"},{"key":"37_CR4","unstructured":"KNX: KNX Smart Home and Building Solutions. Global. Secure. https:\/\/www.knx.org\/knx-en\/for-your-home\/. Accessed on 12 Nov 2020"},{"issue":"1","key":"37_CR5","doi-asserted-by":"publisher","first-page":"71","DOI":"10.3233\/AIS-180508","volume":"11","author":"M Gams","year":"2019","unstructured":"Gams, M., Gu, I.Y.H., H\u00e4rm\u00e4, A., Mu\u00f1oz, A., Tam, V.: Artificial intelligence and ambient intelligence. J. Ambient Intell. Smart Environ. 11(1), 71\u201386 (2019)","journal-title":"J. Ambient Intell. Smart Environ."},{"key":"37_CR6","doi-asserted-by":"crossref","unstructured":"Hussain, M.Z., Ullah, Z., Hassan, T., Hasan, M.Z.: Ambient intelligence. In: LGURJCSIT, vol. 2, pp. 15\u201320 (2018)","DOI":"10.54692\/lgurjcsit.2018.020456"},{"key":"37_CR7","doi-asserted-by":"crossref","unstructured":"Mart\u00edn, A.A.S., Guerrero, E.G., Santamar\u00eda, L.E.B.: Prospective integration between Environmental Intelligence (AMI), Data Analytics (DA), and Internet of Things (IoT). In: Congreso Internacional de Innovaci\u00f3n y Tendencias en Ingenieria (CONIITI), pp. 1\u20136, IEEE (2019)","DOI":"10.1109\/CONIITI48476.2019.8960890"},{"key":"37_CR8","doi-asserted-by":"publisher","unstructured":"Crandall, J.W., Oudah, M., Tennom, et al.: Cooperating with machines. Nat. Commun.\u00a09,\u00a0233 (2018). https:\/\/doi.org\/10.1038\/s41467-017-02597-8","DOI":"10.1038\/s41467-017-02597-8"},{"issue":"11","key":"37_CR9","doi-asserted-by":"publisher","first-page":"517","DOI":"10.1038\/s42256-019-0113-5","volume":"1","author":"F Ishowo-Oloko","year":"2019","unstructured":"Ishowo-Oloko, F., Bonnefon, J.F., Soroye, Z., Crandall, J., Rahwan, I., Rahwan, T.: Behavioural evidence for a transparency-efficiency tradeoff in human-machine cooperation. Nat. Mach. Intell. 1(11), 517\u2013521 (2019)","journal-title":"Nat. Mach. Intell."},{"key":"37_CR10","unstructured":"Pierr, M., Lemoine, P.: Human-machine cooperation: adaptability of shared functions between humans and machines - design and evaluation aspects. In Eng. Sciences. U. Polytechnique Hauts-de-France (2020). https:\/\/hal.archives-ouvertes.fr\/tel-02959402"},{"key":"37_CR11","doi-asserted-by":"crossref","first-page":"144","DOI":"10.18421\/TEM91-20","volume":"9","author":"F Sapundzhi","year":"2020","unstructured":"Sapundzhi, F.: A survey of KNX implementation in building automation. TEM J. 9, 144\u2013148 (2020)","journal-title":"TEM J."},{"key":"37_CR12","doi-asserted-by":"crossref","unstructured":"Feki, E., Kassab, K., Mami, A.: Integration of the small board computers Rasp berry PI in home automation based on KNX protocol. In: IEEE 19th Mediterranean Microwave Symposium (MMS), pp. 1\u20134 (2019)","DOI":"10.1109\/MMS48040.2019.9157317"},{"key":"37_CR13","doi-asserted-by":"crossref","unstructured":"Yumang, A., Abando, M., Dios, E.: Far-field speech-controlled smart classroom with natural language processing built under KNX standard for appliance control. In: International Conference on Computer and Automation Engineering, pp. 219\u2013223 (2020)","DOI":"10.1145\/3384613.3384627"},{"key":"37_CR14","unstructured":"Alpaydin, E.: Introduction to Machine Learning. MIT Press (2020)"},{"key":"37_CR15","unstructured":"Sachan, A.: Human pose estimation using deep learning in OpenCV. https:\/\/cv-tricks.com\/pose-estimation\/using-deep-learning-in-opencv\/. Accessed on 01 July 2020"},{"key":"37_CR16","unstructured":"Sawant, C.: Human activity recognition with openpose and Long Short-Term Memory on real time images (No. 2297). EasyChair (2020)"},{"key":"37_CR17","unstructured":"Yunus, A. P., Shirai, N.C., Morita, K., Wakabayashi, T.: Human Motion Prediction by 2D Human Pose Estimation using OpenPose (No. 2580). EasyChair (2020)"},{"issue":"1","key":"37_CR18","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1109\/tpami.2019.2929257","volume":"43","author":"Z Cao","year":"2021","unstructured":"Cao, Z., Hidalgo, G., Simon, T., Wei, S.E., Sheikh, Y.: OpenPose: realtime multi-person 2D pose estimation using part affinity fields. IEEE Trans. PAMI 43(1), 172\u2013186 (2021). https:\/\/doi.org\/10.1109\/tpami.2019.2929257","journal-title":"IEEE Trans. PAMI"},{"key":"37_CR19","doi-asserted-by":"crossref","unstructured":"Chikano, M., Tomiyasu, F., Awai, S., Hirai, Y., Konno, T.: Person matching technology using gait information of 2D pose estimation. In: 2020 IEEE 2nd Global Conf. on Life Sciences and Technologies (LifeTech), pp. 140\u2013144. IEEE (2020)","DOI":"10.1109\/LifeTech48969.2020.1570614994"},{"key":"37_CR20","doi-asserted-by":"crossref","unstructured":"Satake, H., Tani, R., Shigeno, H.: A task placement system for face recognition applications in edge computing. In: 2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC), pp. 1\u20136. IEEE (2020)","DOI":"10.1109\/CCNC46108.2020.9045194"},{"key":"37_CR21","doi-asserted-by":"publisher","unstructured":"Baltanas, S., Sarmiento, J., Jimenez, J.: A face recognition system for assistive robots. In: Proceedings of the 3rd International Conference on Applications of Intelligent Systems, Art. 29, pp. 1\u20136 (2020). https:\/\/doi.org\/10.1145\/3378184.3378225","DOI":"10.1145\/3378184.3378225"},{"key":"37_CR22","unstructured":"Bellotto, N., Carmona, M., Cosar, S.: ENRICHME integration of ambient intelligence and robotics for AAL. In: Wellbeing AI: From Machine Learning to Subjectivity Oriented Computing, Technical Report SS-17\u201308 (2017)"},{"key":"37_CR23","doi-asserted-by":"crossref","unstructured":"Daher, M., Najjar, M., Diab, A., Khalil, M., Dib, A., Charpillet, F.: Ambient assistive living system using RGB-D camera. In 4th International Conference on Advances in Biomedical Engineering (ICABME), pp. 1\u20134 (2017)","DOI":"10.1109\/ICABME.2017.8167536"},{"key":"37_CR24","doi-asserted-by":"publisher","unstructured":"Chen, W., Jiang, Z., Guo, H., Ni, X.: Fall detection based on key points of human-skeleton using OpenPose. Ing.: Symmetry 12(5), 744 (2020). https:\/\/doi.org\/10.3390\/sym12050744","DOI":"10.3390\/sym12050744"},{"key":"37_CR25","first-page":"69","volume":"23","author":"TS Kavya","year":"2020","unstructured":"Kavya, T.S., Jang, Y.M., Tsogtbaatar, E., Cho, S.B.: Fall detection system for elderly people using vision-based analysis. Sci. Tech. 23, 69\u201383 (2020)","journal-title":"Sci. Tech."},{"key":"37_CR26","doi-asserted-by":"publisher","first-page":"5382","DOI":"10.1007\/s11227-019-03082-3","volume":"76","author":"SH Kim","year":"2020","unstructured":"Kim, S.H., Jang, S.W., Park, J.H.: Robust hand pose estimation using visual sensor in IoT environment. J. Supercomput. 76, 5382\u20135401 (2020). https:\/\/doi.org\/10.1007\/s11227-019-03082-3","journal-title":"J. Supercomput."},{"key":"37_CR27","doi-asserted-by":"publisher","unstructured":"Palsa, J., Vokorokos, L., Bilanova., Z.: User interface of smart environment based on human body gestures. In: IEEE 18th World Symposium on Applied Machine Intelligence and Informatics (SAMI), pp. 165\u2013170 (2020). https:\/\/doi.org\/10.1007\/s11227-019-03082-3","DOI":"10.1007\/s11227-019-03082-3"},{"key":"37_CR28","doi-asserted-by":"publisher","unstructured":"Hern\u00e1ndez, D., Calleros J.M., Garc\u00eda J., Vizzuett L.: Gesture-based interaction for virtual reality environments through user-defined commands. In: Human-Computer Interaction. HCI-COLLAB 2018. Communications in Computer and Information Science, vol. 847, pp. 143\u2013157 (2019). https:\/\/doi.org\/10.1007\/978-3-030-05270-6_11","DOI":"10.1007\/978-3-030-05270-6_11"},{"key":"37_CR29","unstructured":"XKNX: Asynchronous Python Library for KNX. https:\/\/xknx.io\/. Accessed on 12 Nov 2020"},{"key":"37_CR30","unstructured":"Guo, J., et al.: GluonCV and GluonNLP: Deep learning in computer vision and natural language processing. J. Mach. Learn. Res. 21, 1\u20137 (2020)"},{"key":"37_CR31","unstructured":"GluonCV, State-of-the-art Deep Learning Algorithms in Computer Vision. https:\/\/cv.gluon.ai\/. Accessed on 12 Nov 2020"},{"key":"37_CR32","doi-asserted-by":"crossref","unstructured":"Xiao, B., Wu, H., Wei, Y.: Simple baselines for human pose estimation and tracking. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 466\u2013481 (2018)","DOI":"10.1007\/978-3-030-01231-1_29"}],"container-title":["Lecture Notes in Computer Science","Universal Access in Human-Computer Interaction. Access to Media, Learning and Assistive Environments"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-78095-1_37","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,2]],"date-time":"2025-07-02T22:26:50Z","timestamp":1751495210000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-78095-1_37"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030780944","9783030780951"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-78095-1_37","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"3 July 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HCII","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Human-Computer Interaction","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 July 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 July 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"hcii2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2021.hci.international\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}