{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:28:51Z","timestamp":1760239731626,"version":"build-2065373602"},"reference-count":21,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2020,12,17]],"date-time":"2020-12-17T00:00:00Z","timestamp":1608163200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Here, we propose a novel application of a low-cost robust gravimetric system for public place access monitoring purposes. The proposed solution is intended to be exploited in a multi-sensor scenario, where heterogeneous information, coming from different sources (e.g., metal detectors and surveillance cameras), are collected in a central data fusion unit to obtain a more detailed and accurate evaluation of notable events. Specifically, the word \u201cnotable\u201d refers essentially to two event categories: the first category is represented by irregular events, corresponding typically to multiple people passing together through a security gate; the second category includes some event subsets, whose notification can be interesting for assistance provision (in the case of people with disabilities), or for statistical analysis. The employed gravimetric sensor, compared to other devices existing in the literature, exhibits a simple scalable robust structure, made up of an array of rigid steel plates, each laid on four load cells. We developed a tailored hardware and software to individually acquire the load cell signals, and to post-process the data to formulate a classification of the notable events. The results are encouraging, showing a remarkable detectability of irregularities (95.3% of all the test cases) and a satisfactory identification of the other event types.<\/jats:p>","DOI":"10.3390\/s20247225","type":"journal-article","created":{"date-parts":[[2020,12,17]],"date-time":"2020-12-17T10:42:47Z","timestamp":1608201767000},"page":"7225","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Working Principle and Performance of a Scalable Gravimetric System for the Monitoring of Access to Public Places"],"prefix":"10.3390","volume":"20","author":[{"given":"Tommaso","family":"Addabbo","sequence":"first","affiliation":[{"name":"Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0916-1516","authenticated-orcid":false,"given":"Ada","family":"Fort","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8388-2210","authenticated-orcid":false,"given":"Matteo","family":"Intravaia","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy"}]},{"given":"Marco","family":"Mugnaini","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy"}]},{"given":"Marco","family":"Tani","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2509-6566","authenticated-orcid":false,"given":"Valerio","family":"Vignoli","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy"}]},{"given":"Stefano","family":"De Muro","sequence":"additional","affiliation":[{"name":"Rete Ferroviaria Italiana S.p.A. Direzione Protezione Aziendale, Piazza della Croce Rossa 1, 00161 Roma, Italy"}]},{"given":"Marco","family":"Tesei","sequence":"additional","affiliation":[{"name":"Rete Ferroviaria Italiana S.p.A. Direzione Protezione Aziendale, Piazza della Croce Rossa 1, 00161 Roma, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Oh, H.-W., Yun, J.-K., and Huh, J.-D. (2016, January 5\u20137). Implementation of CoM footboard sensor for lower limb rehabilitation. Proceedings of the 2016 IEEE 6th International Conference on Consumer Electronics\u2014Berlin (ICCE-Berlin), Berlin, Germany.","DOI":"10.1109\/ICCE-Berlin.2016.7684710"},{"key":"ref_2","unstructured":"Middleton, L., Buss, A., Bazin, A., and Nixon, M. (2006, January 17\u201318). A Floor Sensor System for Gait Recognition. Proceedings of the Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AutoID\u201905), Buffalo, NY, USA."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Muheidat, F., Tyrer, H.W., Popescu, M., and Rantz, M. (2017, January 13\u201315). Estimating walking speed, stride length, and stride time using a passive floor based electronic scavenging system. Proceedings of the 2017 IEEE Sensors Applications Symposium (SAS), Glassboro, NJ, USA.","DOI":"10.1109\/SAS.2017.7894112"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-020-18471-z","article-title":"Deep learning enabled smart mats as a scalable floor monitoring system","volume":"11","author":"Shi","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1007\/s11517-016-1546-1","article-title":"Selection of clinical features for pattern recognition applied to gait analysis","volume":"55","author":"Altilio","year":"2017","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Beyea, J., McGibbon, C.A., Sexton, A., Noble, J., and O\u2019Connell, C. (2017). Convergent Validity of a Wearable Sensor System for Measuring Sub-Task Performance during the Timed Up-and-Go Test. Sensors, 17.","DOI":"10.3390\/s17040934"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Guaitolini, M., Federica, A., Mannini, A., Micera, S., Vito, M., and Sabatini, A.M. (2019). Ambulatory Assessment of the Dynamic Margin of Stability Using an Inertial Sensor Network. Sensors, 19.","DOI":"10.3390\/s19194117"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1447","DOI":"10.1109\/JSEN.2010.2045158","article-title":"People Identification Using Floor Pressure Sensing and Analysis","volume":"10","author":"Qian","year":"2010","journal-title":"IEEE Sens. J."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Al-Naimi, I., Wong, C.B., Moore, P., and Chen, X. (2014, January 1\u20133). Advanced approach for indoor identification and tracking using smart floor and pyroelectric infrared sensors. Proceedings of the 2013 IEEE International Conference on Computer Vision Workshops, Irbid, Jordan.","DOI":"10.1109\/IACS.2014.6841966"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Al-Naimi, I., and Wong, C.B. (2017, January 4\u20136). Indoor human detection and tracking using advanced smart floor. Proceedings of the 2017 8th International Conference on Information and Communication Systems (ICICS), Irbid, Jordan.","DOI":"10.1109\/IACS.2017.7921942"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4239","DOI":"10.1109\/JSEN.2017.2703633","article-title":"Low-Cost Intelligent Carpet System for Footstep Detection","volume":"17","author":"Agrawal","year":"2017","journal-title":"IEEE Sens. J."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1026","DOI":"10.1109\/JSEN.2015.2493122","article-title":"Localization of Humans, Objects, and Robots Interacting on Load-Sensing Floors","volume":"16","author":"Andries","year":"2016","journal-title":"IEEE Sens. J."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Heydarzadeh, M., Birjandtalab, J., Pouyan, M.B., Nourani, M., and Ostadabbas, S. (2017, January 16\u201319). Gaits analysis using pressure image for subject identification. Proceedings of the 2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), Orlando, FL, USA.","DOI":"10.1109\/BHI.2017.7897273"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Zhou, B., Singh, M.S., Doda, S., Yildirim, M., Cheng, J., and Lukowicz, P. (2017, January 13\u201317). The carpet knows: Identifying people in a smart environment from a single step. Proceedings of the 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Kona, HI, USA.","DOI":"10.1109\/PERCOMW.2017.7917618"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Terrier, P. (2020). Gait Recognition via Deep Learning of the Center-of-Pressure Trajectory. Appl. Sci., 10.","DOI":"10.3390\/app10030774"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"187353","DOI":"10.1109\/ACCESS.2020.3029971","article-title":"CapLoc: Capacitive Sensing Floor for Device-Free Localization and Fall Detection","volume":"8","author":"Faulkner","year":"2020","journal-title":"IEEE Access"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Addabbo, T., Fort, A., Mugnaini, M., Vignoli, V., Intravaia, M., Tani, M., De Muro, S., and Tesei, M. (2020, January 3\u20135). Low-cost, robust gravimetric system for enhanced security of accesses to public places. Proceedings of the 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT, Roma, Italy.","DOI":"10.1109\/MetroInd4.0IoT48571.2020.9138253"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1016\/j.sna.2018.11.047","article-title":"Realization and performance assessment of a force-sensing based smart floor panel for indoor localization applications","volume":"285","author":"Cheng","year":"2019","journal-title":"Sens. Actuators A Phys."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Krishnamurthi, R., Kumar, A., Gopinathan, D., Nayyar, A., and Qureshi, B. (2020). An Overview of IoT Sensor Data Processing, Fusion, and Analysis Techniques. Sensors, 20.","DOI":"10.3390\/s20216076"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.5194\/jsss-8-1-2019","article-title":"Flexible piezoresistive sensor matrix based on a carbon nanotube PDMS composite for dynamic pressure distribution measurement","volume":"8","author":"Ramalingame","year":"2019","journal-title":"J. Sens. Sens. Syst."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"26126","DOI":"10.1021\/acsami.7b08526","article-title":"Smart Floor with Integrated Triboelectric Nanogenerator As Energy Harvester and Motion Sensor","volume":"9","author":"He","year":"2017","journal-title":"ACS Appl. Mater. Interfaces"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/24\/7225\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:46:16Z","timestamp":1760179576000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/24\/7225"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,17]]},"references-count":21,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2020,12]]}},"alternative-id":["s20247225"],"URL":"https:\/\/doi.org\/10.3390\/s20247225","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2020,12,17]]}}}