{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T15:38:07Z","timestamp":1783697887993,"version":"3.55.0"},"reference-count":80,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2018,2,2]],"date-time":"2018-02-02T00:00:00Z","timestamp":1517529600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>This paper discusses how the state-of-the-art techniques in cyber-physical systems facilitate building smart warehouses to achieve the promising vision of industry 4.0. We focus on four significant issues when applying CPS techniques in smart warehouses. First, efficient CPS data collection: when limited communication bandwidth meets numerous CPS devices, we need to make more effort to study efficient wireless communication scheduling strategies. Second, accurate and robust localization: localization is the basis for many fundamental operations in smart warehouses, but still needs to be improved from various aspects like accuracy and robustness. Third, human activity recognition: human activity recognition can be applied in human\u2013computer interaction for remote machine operations. Fourth, multi-robot collaboration: smart robots will take the place of humans to accomplish most tasks particularly in a harsh environment, and smart and fully-distributed robot collaborating algorithms should be investigated. Finally, we point out some challenging issues in the future CPS-based smart warehouse, which could open some new research directions.<\/jats:p>","DOI":"10.3390\/computers7010013","type":"journal-article","created":{"date-parts":[[2018,2,2]],"date-time":"2018-02-02T06:45:40Z","timestamp":1517553940000},"page":"13","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":91,"title":["CPS-Based Smart Warehouse for Industry 4.0: A Survey of the Underlying Technologies"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4746-5599","authenticated-orcid":false,"given":"Xiulong","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiannong","family":"Cao","sequence":"additional","affiliation":[{"name":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanni","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4727-4856","authenticated-orcid":false,"given":"Shan","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,2,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Jabbar, S., Khan, M., Silva, B.N., and Han, K. (2016). A REST-based industrial web of things\u2019 framework for smart warehousing. J. Supercomput., 1\u201315.","DOI":"10.1007\/s11227-016-1937-y"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.mfglet.2014.12.001","article-title":"A cyber-physical systems architecture for industry 4.0-based manufacturing systems","volume":"3","author":"Lee","year":"2015","journal-title":"Manuf. Lett."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"11734","DOI":"10.3390\/s120911734","article-title":"Overview and Evaluation of Bluetooth Low Energy: An Emerging Low-Power Wireless Technology","volume":"12","author":"Gomez","year":"2012","journal-title":"Sensors"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1109\/MNET.2017.1700043","article-title":"Pinpointing Anomaly RFID Tags: Situation and Opportunities","volume":"31","author":"Liu","year":"2017","journal-title":"IEEE Netw."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1109\/TC.2013.197","article-title":"Completely Pinpointing the Missing RFID Tags in a Time-Efficient Way","volume":"64","author":"Liu","year":"2015","journal-title":"IEEE Trans. Comput."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1046","DOI":"10.1109\/TCOMM.2014.011914.130089","article-title":"A Multiple Hashing Approach to Complete Identification of Missing RFID Tags","volume":"62","author":"Liu","year":"2014","journal-title":"IEEE Trans. Commun."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Liu, X., Zhang, S., Bu, K., and Xiao, B. (2012, January 8\u201311). Complete and fast unknown tag identification in large RFID systems. Proceedings of the 2012 IEEE 9th International Conference on Mobile Adhoc and Sensor Systems (MASS), Las Vegas, NV, USA.","DOI":"10.1109\/MASS.2012.6502501"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1432","DOI":"10.1109\/TCOMM.2015.2402660","article-title":"Sampling Bloom Filter-Based Detection of Unknown RFID Tags","volume":"63","author":"Liu","year":"2015","journal-title":"IEEE Trans. Commun."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3145","DOI":"10.1109\/TPDS.2013.2297103","article-title":"Efficient Unknown Tag Identification Protocols in Large-Scale RFID Systems","volume":"25","author":"Liu","year":"2014","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Kodialam, M.S., and Nandagopal, T. (2006, January 23\u201329). Fast and reliable estimation schemes in RFID systems. Proceedings of the 12th Annual International Conference on Mobile Computing and Networking, Los Angeles, CA, USA.","DOI":"10.1145\/1161089.1161126"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1109\/TNET.2014.2298039","article-title":"Fast and Accurate Estimation of RFID Tags","volume":"23","author":"Shahzad","year":"2015","journal-title":"IEEE\/ACM Trans. Netw."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Li, T., Wu, S.S., Chen, S., and Yang, M.C.K. (2010, January 14\u201319). Energy Efficient Algorithms for the RFID Estimation Problem. Proceedings of the 2010 IEEE INFOCOM, San Diego, CA, USA.","DOI":"10.1109\/INFCOM.2010.5461947"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1763","DOI":"10.1109\/TMC.2011.238","article-title":"PET: Probabilistic Estimating Tree for Large-Scale RFID Estimation","volume":"11","author":"Zheng","year":"2012","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Xiao, Q., Xiao, B., and Chen, S. (2013, January 14\u201319). Differential estimation in dynamic RFID systems. Proceedings of the 2013 IEEE INFOCOM, Turin, Italy.","DOI":"10.1109\/INFCOM.2013.6566782"},{"key":"ref_15","unstructured":"Gong, W., Liu, K., Miao, X., Ma, Q., Yang, Z., and Liu, Y. (August, January 29). Informative counting: Fine-grained batch authentication for large-scale RFID systems. Proceedings of the Fourteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing, Bangalore, India."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Liu, X., Xiao, B., Li, K., Wu, J., Liu, A.X., Qi, H., and Xie, X. (May, January 26). RFID cardinality estimation with blocker tags. Proceedings of the 2015 IEEE Conference on Computer Communications (INFOCOM), Hong Kong, China.","DOI":"10.1109\/INFOCOM.2015.7218548"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1109\/TNET.2016.2595571","article-title":"RFID Estimation With Blocker Tags","volume":"25","author":"Liu","year":"2017","journal-title":"IEEE\/ACM Trans. Netw."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1109\/TNET.2016.2594481","article-title":"Multi-Category RFID Estimation","volume":"25","author":"Liu","year":"2017","journal-title":"IEEE\/ACM Trans. Netw."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1023\/B:WINE.0000044029.06344.dd","article-title":"LANDMARC: Indoor Location Sensing Using Active RFID","volume":"10","author":"Ni","year":"2004","journal-title":"Wirel. Netw."},{"key":"ref_20","unstructured":"Shangguan, L., Yang, Z., Liu, A.X., Zhou, Z., and Liu, Y. (2015, January 4\u20136). Relative Localization of RFID Tags using Spatial-Temporal Phase Profiling. Proceedings of the 12th USENIX Symposium on Networked Systems Design and Implementation (NSDI\u201915), Oakland, CA, USA."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Azzouzi, S., Cremer, M., Dettmar, U., Kronberger, R., and Knie, T. (2011, January 12\u201314). New Measurement Results for the Localization of UHF RFID Transponders Using an Angle of Arrival (AoA) Approach. Proceedings of the IEEE International Conference on RFID, Orlando, FL, USA.","DOI":"10.1109\/RFID.2011.5764607"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Wang, J., and Katabi, D. (2013, January 12\u201316). Dude, where\u2019s my card? RFID positioning that works with multipath and non-line of sight. Proceedings of the ACM SIGCOMM 2013, Hong Kong, China.","DOI":"10.1145\/2486001.2486029"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Yang, L., Chen, Y., Li, X., Xiao, C., Li, M., and Liu, Y. (2014, January 7\u201311). Tagoram: Real-time tracking of mobile RFID tags to high precision using COTS devices. Proceedings of the 20th Annual International Conference on Mobile Computing and Networking, Maui, HI, USA.","DOI":"10.1145\/2639108.2639111"},{"key":"ref_24","unstructured":"Liu, T., Yang, L., Lin, Q., Guo, Y., and Liu, Y. (May, January 27). Anchor-free backscatter positioning for RFID tags with high accuracy. Proceedings of the IEEE INFOCOM, Toronto, ON, Canada."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Liu, J., Zhu, F., Wang, Y., Wang, X., Pan, Q., and Chen, L. (2017, January 1\u20134). RF-scanner: Shelf scanning with robot-assisted RFID systems. Proceedings of the IEEE INFOCOM, Atlanta, GA, USA.","DOI":"10.1109\/INFOCOM.2017.8056985"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Jiang, S., Cao, J., Liu, Y., Chen, J., and Liu, X. (2016, January 1\u20134). Programming Large-Scale Multi-Robot System with Timing Constraints. Proceedings of the 25th International Conference on Computer Communication and Networks (ICCCN), Waikoloa, HI, USA.","DOI":"10.1109\/ICCCN.2016.7568563"},{"key":"ref_27","unstructured":"Garey, M.R., and Johnson, D.S. (1979). Computers and Intractability: A Guide to the Theory of NP-Completeness, W.H. Freeman and Company."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Liu, L., and Shell, D.A. (2013, January 24\u201328). Optimal Market-based Multi-Robot Task Allocation via Strategic Pricing. Proceedings of the Robotics: Science and Systems, Berlin, Germany.","DOI":"10.15607\/RSS.2013.IX.033"},{"key":"ref_29","unstructured":"Schneider, E., Balas, O., Ozgelen, A.T., Sklar, E.I., and Parsons, S. (2014, January 5\u20139). An empirical evaluation of auction-based task allocation in multi-robot teams. Proceedings of the 2014 International Conference on Autonomous Agents and Multi-Agent Systems, Paris, France."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"974","DOI":"10.1109\/TCYB.2016.2535153","article-title":"A Bio-Inspired Approach to Task Assignment of Swarm Robots in 3-D Dynamic Environments","volume":"47","author":"Yi","year":"2017","journal-title":"IEEE Trans. Cybern."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1453","DOI":"10.1016\/j.robot.2014.05.015","article-title":"Local interactions over global broadcasts for improved task allocation in self-organized multi-robot systems","volume":"62","author":"Sarker","year":"2014","journal-title":"Robot. Auton. Syst."},{"key":"ref_32","unstructured":"Gombolay, M.C., Wilcox, R., and Shah, J.A. (June, January 24). Fast Scheduling of Multi-Robot Teams with Temporospatial Constraints. Proceedings of the Robotics: Science and Systems IX, Berlin, Germany."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Riccio, F., Borzi, E., Gemignani, G., and Nardi, D. (2016, January 9\u201314). Multi-robot search for a moving target: Integrating world modeling, task assignment and context. Proceedings of the 2016 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea.","DOI":"10.1109\/IROS.2016.7759298"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1321","DOI":"10.1007\/s10514-016-9579-8","article-title":"Distributed on-line dynamic task assignment for multi-robot patrolling","volume":"41","author":"Farinelli","year":"2017","journal-title":"Auton. Robot."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.robot.2016.12.006","article-title":"Bio-inspired self-organising multi-robot pattern formation: A review","volume":"91","author":"Oh","year":"2017","journal-title":"Robot. Auton. Syst."},{"key":"ref_36","first-page":"24","article-title":"A Survey and Comparative Study of Hard and Soft Real-Time Dynamic Resource Allocation Strategies for Multi-\/Many-Core Systems","volume":"50","author":"Singh","year":"2017","journal-title":"ACM Comput. Surv."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1696","DOI":"10.1109\/LRA.2017.2665693","article-title":"Real-Time Motion Planning for Aerial Videography With Real-Time With Dynamic Obstacle Avoidance and Viewpoint Optimization","volume":"2","author":"Domahidi","year":"2017","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Flocchini, P., Prencipe, G., and Santoro, N. (2012). Distributed Computing by Oblivious Mobile Robots. Synthesis Lectures on Distributed Computing Theory, Morgan & Claypool Publishers.","DOI":"10.1007\/978-3-031-02008-7"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.jda.2015.10.005","article-title":"Fault-tolerant gathering of asynchronous oblivious mobile robots under one-axis agreement","volume":"36","author":"Bhagat","year":"2016","journal-title":"J. Discret. Algorithms"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1137\/140958682","article-title":"Pattern Formation by Oblivious Asynchronous Mobile Robots","volume":"44","author":"Fujinaga","year":"2015","journal-title":"SIAM J. Comput."},{"key":"ref_41","unstructured":"Canepa, D., D\u00e9fago, X., Izumi, T., and Potop-Butucaru, M. (2016, January 7\u201310). Flocking with Oblivious Robots. Proceedings of the 8th International Symposium, SSS 2016, Lyon, France."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1016\/j.ic.2016.09.004","article-title":"Gathering of oblivious robots on infinite grids with minimum traveled distance","volume":"254","author":"Navarra","year":"2017","journal-title":"Inf. Comput."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.tcs.2014.06.045","article-title":"Gathering of robots on anonymous grids and trees without multiplicity detection","volume":"610","author":"Klasing","year":"2016","journal-title":"Theor. Comput. Sci."},{"key":"ref_44","unstructured":"Datta, S., Dutta, A., Chaudhuri, S.G., and Mukhopadhyaya, K. (2013, January 5\u20138). Circle Formation by Asynchronous Transparent Fat Robots. Proceedings of the 9th International Conference, ICDCIT 2013, Bhubaneswar, India."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1007\/s00446-016-0291-x","article-title":"Distributed computing by mobile robots: Uniform circle formation","volume":"30","author":"Flocchini","year":"2017","journal-title":"Distrib. Comput."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Jiang, S., Cao, J., Wang, J., Stojmenovic, M., and Bourgeois, J. (August, January 31). Uniform Circle Formation by Asynchronous Robots: A Fully-Distributed Approach. Proceedings of the 2017 26th International Conference on Computer Communication and Networks (ICCCN), Vancouver, BC, Canada.","DOI":"10.1109\/ICCCN.2017.8038468"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1007\/s00446-014-0220-9","article-title":"Forming sequences of geometric patterns with oblivious mobile robots","volume":"28","author":"Das","year":"2015","journal-title":"Distrib. Comput."},{"key":"ref_48","unstructured":"Yamauchi, Y., and Yamashita, M. (2014, January 12\u201315). Randomized Pattern Formation Algorithm for Asynchronous Oblivious Mobile Robots. Proceedings of the 28th International Symposium, DISC 2014, Austin, TX, USA."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1016\/j.dam.2003.11.010","article-title":"Coordination without communication: The case of the flocking problem","volume":"144","author":"Gervasi","year":"2004","journal-title":"Discret. Appl. Math."},{"key":"ref_50","unstructured":"Canepa, D., and Potop-Butucaru, M.G. (2007, January 14\u201316). Stabilizing Flocking via Leader Election in Robot Networks. Proceedings of the 9th International Symposium (SSS 2007), Paris, France."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1337","DOI":"10.1109\/TPAMI.2003.1233909","article-title":"Detecting Moving Objects, Ghosts, Shadows in Video Streams","volume":"25","author":"Cucchiara","year":"2003","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_52","unstructured":"Seki, M., Fujiwara, H., and Sumi, K. (2000, January 4\u20136). A robust background subtraction method for changing background. Proceedings of the Fifth IEEE Workshop on Applications of Computer Vision, Palm Springs, CA, USA."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Ke, Y., Sukthankar, R., and Hebert, M. (2007, January 17\u201322). Spatio-temporal Shape and Flow Correlation for Action Recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, MN, USA.","DOI":"10.1109\/CVPR.2007.383512"},{"key":"ref_54","unstructured":"Shechtman, E., and Irani, M. (2005, January 20\u201325). Space-Time Behavior Based Correlation. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, CA, USA."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Kumari, S., and Mitra, S.K. (2011, January 15\u201317). Human action recognition using DFT. Proceedings of the 2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), Hubli, India.","DOI":"10.1109\/NCVPRIPG.2011.58"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Sedai, S., Bennamoun, M., and Huynh, D.Q. (2009, January 1\u20133). Context-Based Appearance Descriptor for 3D Human Pose Estimation from Monocular Images. Proceedings of the Digital Image Computing: Techniques and Applications, Melbourne, Australia.","DOI":"10.1109\/DICTA.2009.81"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Dargazany, A., and Nicolescu, M. (2012, January 16\u201318). Human Body Parts Tracking Using Torso Tracking: Applications to Activity Recognition. Proceedings of the 2012 Ninth International Conference on Information Technology: New Generations (ITNG), Las Vegas, NV, USA.","DOI":"10.1109\/ITNG.2012.132"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1109\/TPAMI.2008.35","article-title":"Human Pose Tracking in Monocular Sequence Using Multilevel Structured Models","volume":"31","author":"Lee","year":"2009","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Sempena, S., Maulidevi, N.U., and Aryan, P.R. (2011, January 17\u201319). Human action recognition using Dynamic Time Warping. Proceedings of the 2011 International Conference on Electrical Engineering and Informatics (ICEEI), Bandung, Indonesia.","DOI":"10.1109\/ICEEI.2011.6021605"},{"key":"ref_60","unstructured":"Thuc, H.L., Ke, S., Hwang, J., van Tuan, P., and Chau, T.N. (2012, January 10\u201312). Quasi-periodic action recognition from monocular videos via 3D human models and cyclic HMMs. Proceedings of the 2012 International Conference on Advanced Technologies for Communications (ATC), Hanoi, Vietnam."},{"key":"ref_61","unstructured":"Du, Y., Wang, W., and Wang, L. (2015, January 7\u201312). Hierarchical recurrent neural network for skeleton based action recognition. Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Ch\u00e9ron, G., Laptev, I., and Schmid, C. (2015, January 7\u201313). P-CNN: Pose-Based CNN Features for Action Recognition. Proceedings of the 2015 IEEE International Conference on Computer Vision (ICCV), Santiago, Chile.","DOI":"10.1109\/ICCV.2015.368"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Iglesias, J., Cano, J., Bernardos, A.M., and Casar, J.R. (2011, January 21\u201325). A ubiquitous activity-monitor to prevent sedentariness. Proceedings of the 2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), Seattle, WA, USA.","DOI":"10.1109\/PERCOMW.2011.5766894"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1109\/TITB.2005.856863","article-title":"Activity Classification Using Realistic Data From Wearable Sensors","volume":"10","author":"Ermes","year":"2006","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Jatoba, L.C., Grossmann, U., Kunze, C., Ottenbacher, J., and Stork, W. (2008, January 20\u201325). Context-aware mobile health monitoring: Evaluation of different pattern recognition methods for classification of physical activity. Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vancouver, BC, Canada.","DOI":"10.1109\/IEMBS.2008.4650398"},{"key":"ref_66","unstructured":"Zhou, B., Lapedriza, \u00c0., Xiao, J., Torralba, A., and Oliva, A. (2014, January 8\u201313). Learning Deep Features for Scene Recognition using Places Database. Proceedings of the 27th International Conference on Neural Information Processing Systems, Montreal, QC, Canada."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Wang, Y., Liu, J., Chen, Y., Gruteser, M., Yang, J., and Liu, H. (2014, January 7\u201311). E-eyes: Device-free location-oriented activity identification using fine-grained WiFi signatures. Proceedings of the 20th Annual International Conference on Mobile Computing and Networking, Maui, HI, USA.","DOI":"10.1145\/2639108.2639143"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1109\/TMC.2016.2557792","article-title":"WiFall: Device-Free Fall Detection by Wireless Networks","volume":"16","author":"Wang","year":"2017","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Liu, X., Cao, J., Tang, S., and Wen, J. (2014, January 2\u20135). Wi-Sleep: Contactless Sleep Monitoring via WiFi Signals. Proceedings of the 35th Real-Time Systems Symposium, Rome, Italy.","DOI":"10.1109\/RTSS.2014.30"},{"key":"ref_70","unstructured":"Hong, F., Wang, X., Yang, Y., Zong, Y., Zhang, Y., and Guo, Z. (December, January 28). WFID: Passive Device-free Human Identification Using WiFi Signal. Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, Hiroshima, Japan."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Shi, C., Liu, J., Liu, H., and Chen, Y. (2017, January 10\u201314). Smart User Authentication through Actuation of Daily Activities Leveraging WiFi-enabled IoT. Proceedings of the 18th ACM International Symposium on Mobile Ad Hoc Networking and Computing, Chennai, India.","DOI":"10.1145\/3084041.3084061"},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Li, X., Li, S., Zhang, D., Xiong, J., Wang, Y., and Mei, H. (2016, January 12\u201316). Dynamic-MUSIC: Accurate device-free indoor localization. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Heidelberg, Germany.","DOI":"10.1145\/2971648.2971665"},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Wang, W., Liu, A.X., Shahzad, M., Ling, K., and Lu, S. (2015, January 7\u201311). Understanding and Modeling of WiFi Signal Based Human Activity Recognition. Proceedings of the 21st Annual International Conference on Mobile Computing and Networking, Paris, France.","DOI":"10.1145\/2789168.2790093"},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Wang, H., Zhang, D., Ma, J., Wang, Y., Wang, Y., Wu, D., Gu, T., and Xie, B. (2016, January 12\u201316). Human respiration detection with commodity wifi devices: Do user location and body orientation matter?. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Heidelberg, Germany.","DOI":"10.1145\/2971648.2971744"},{"key":"ref_75","unstructured":"Satoshi, N. (2018, January 30). Bitcoin: A Peer-to-Peer Electronic Cash System. Available online: https:\/\/bitcoin.org\/bitcoin.pdf."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"1832","DOI":"10.1109\/JIOT.2017.2740569","article-title":"Blockchain-Based Dynamic Key Management for Heterogeneous Intelligent Transportation Systems","volume":"4","author":"Lei","year":"2017","journal-title":"IEEE Internet Things J."},{"key":"ref_77","unstructured":"Hou, H. (August, January 31). The Application of Blockchain Technology in E-Government in China. Proceedings of the 26th International Conference on Computer Communication and Networks (ICCCN), Vancouver, BC, Canada."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Turkanovic, M., H\u00f6lbl, M., Kosic, K., Hericko, M., and Kamisalic, A. (2018). EduCTX: A blockchain-based higher education credit platform. IEEE Access.","DOI":"10.1109\/ACCESS.2018.2789929"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1016\/j.compag.2016.07.004","article-title":"A webGIS-based system for real time shelf life prediction","volume":"127","author":"Sciortino","year":"2016","journal-title":"Comput. Electron. Agric."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"1238","DOI":"10.1177\/0278364913495721","article-title":"Reinforcement learning in robotics: A survey","volume":"32","author":"Kober","year":"2013","journal-title":"Int. J. Robot. Res."}],"container-title":["Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-431X\/7\/1\/13\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:53:32Z","timestamp":1760194412000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-431X\/7\/1\/13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,2,2]]},"references-count":80,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2018,3]]}},"alternative-id":["computers7010013"],"URL":"https:\/\/doi.org\/10.3390\/computers7010013","relation":{},"ISSN":["2073-431X"],"issn-type":[{"value":"2073-431X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,2,2]]}}}