{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T07:10:18Z","timestamp":1780470618888,"version":"3.54.1"},"reference-count":62,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,3,24]],"date-time":"2021-03-24T00:00:00Z","timestamp":1616544000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["318927"],"award-info":[{"award-number":["318927"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011688","name":"Electronic Components and Systems for European Leadership","doi-asserted-by":"publisher","award":["877056"],"award-info":[{"award-number":["877056"]}],"id":[{"id":"10.13039\/501100011688","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Infotech Oulu research institute","award":["N\/A"],"award-info":[{"award-number":["N\/A"]}]},{"name":"Future Makers program of the Jane and Aatos Erkko Foundation and the Technology Industries of Finland Centennial Foundation","award":["N\/A"],"award-info":[{"award-number":["N\/A"]}]},{"name":"Tauno T\u00f6nning foundation","award":["personal grant for L.L."],"award-info":[{"award-number":["personal grant for L.L."]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Spatio-temporal interpolation provides estimates of observations in unobserved locations and time slots. In smart cities, interpolation helps to provide a fine-grained contextual and situational understanding of the urban environment, in terms of both short-term (e.g., weather, air quality, traffic) or long term (e.g., crime, demographics) spatio-temporal phenomena. Various initiatives improve spatio-temporal interpolation results by including additional data sources such as vehicle-fitted sensors, mobile phones, or micro weather stations of, for example, smart homes. However, the underlying computing paradigm in such initiatives is predominantly centralized, with all data collected and analyzed in the cloud. This solution is not scalable, as when the spatial and temporal density of sensor data grows, the required transmission bandwidth and computational capacity become unfeasible. To address the scaling problem, we propose EDISON: algorithms for distributed learning and inference, and an edge-native architecture for distributing spatio-temporal interpolation models, their computations, and the observed data vertically and horizontally between device, edge and cloud layers. We demonstrate EDISON functionality in a controlled, simulated spatio-temporal setup with 1 M artificial data points. While the main motivation of EDISON is the distribution of the heavy computations, the results show that EDISON also provides an improvement over alternative approaches, reaching at best a 10% smaller RMSE than a global interpolation and 6% smaller RMSE than a baseline distributed approach.<\/jats:p>","DOI":"10.3390\/s21072279","type":"journal-article","created":{"date-parts":[[2021,3,24]],"date-time":"2021-03-24T21:36:51Z","timestamp":1616621811000},"page":"2279","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["EDISON: An Edge-Native Method and Architecture for Distributed Interpolation"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9475-4839","authenticated-orcid":false,"given":"Lauri","family":"Lov\u00e9n","sequence":"first","affiliation":[{"name":"Center for Ubiquitous Computing, University of Oulu, FI-90014 Oulu, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5856-2899","authenticated-orcid":false,"given":"Tero","family":"L\u00e4hderanta","sequence":"additional","affiliation":[{"name":"Research Unit of Mathematical Sciences, University of Oulu, FI-90014 Oulu, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6404-7241","authenticated-orcid":false,"given":"Leena","family":"Ruha","sequence":"additional","affiliation":[{"name":"Research Unit of Mathematical Sciences, University of Oulu, FI-90014 Oulu, Finland"},{"name":"Natural Resources Institute Finland, FI-90014 Oulu, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3374-671X","authenticated-orcid":false,"given":"Ella","family":"Peltonen","sequence":"additional","affiliation":[{"name":"Center for Ubiquitous Computing, University of Oulu, FI-90014 Oulu, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0565-800X","authenticated-orcid":false,"given":"Ilkka","family":"Launonen","sequence":"additional","affiliation":[{"name":"Research Unit of Mathematical Sciences, University of Oulu, FI-90014 Oulu, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2808-2768","authenticated-orcid":false,"given":"Mikko J.","family":"Sillanp\u00e4\u00e4","sequence":"additional","affiliation":[{"name":"Research Unit of Mathematical Sciences, University of Oulu, FI-90014 Oulu, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1694-9152","authenticated-orcid":false,"given":"Jukka","family":"Riekki","sequence":"additional","affiliation":[{"name":"Center for Ubiquitous Computing, University of Oulu, FI-90014 Oulu, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2428-9948","authenticated-orcid":false,"given":"Susanna","family":"Pirttikangas","sequence":"additional","affiliation":[{"name":"Center for Ubiquitous Computing, University of Oulu, FI-90014 Oulu, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,24]]},"reference":[{"key":"ref_1","unstructured":"United Nations, Department of Economic and Social Affairs, Population Division (2019). World Urbanization Prospects: The 2018 Revision (ST\/ESA\/SER.A\/420), United Nations."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1177\/0020852314564308","article-title":"Governing the smart city: A review of the literature on smart urban governance","volume":"82","author":"Meijer","year":"2016","journal-title":"Int. Rev. Adm. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1089","DOI":"10.1016\/j.procs.2015.05.122","article-title":"Smart city architecture and its applications based on IoT","volume":"52","author":"Gaur","year":"2015","journal-title":"Procedia Comput. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Strohbach, M., Ziekow, H., Gazis, V., and Akiva, N. (2015). Towards a big data analytics framework for IoT and smart city applications. Modeling and Processing for Next-Generation Big-Data Technologies, Springer.","DOI":"10.1007\/978-3-319-09177-8_11"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Angelidou, M., Psaltoglou, A., Komninos, N., Kakderi, C., Tsarchopoulos, P., and Panori, A. (2018). Enhancing sustainable urban development through smart city applications. J. Sci. Technol. Policy Manag., 9.","DOI":"10.1108\/JSTPM-05-2017-0016"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/MC.2011.187","article-title":"Smarter cities and their innovation challenges","volume":"44","author":"Naphade","year":"2011","journal-title":"Computer"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/j.inffus.2019.05.004","article-title":"A survey of data fusion in smart city applications","volume":"52","author":"Lau","year":"2019","journal-title":"Inf. Fusion"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Bokolo, A.J., Majid, M.A., and Romli, A. (2018, January 25\u201326). A trivial approach for achieving Smart City: A way forward towards a sustainable society. Proceedings of the 2018 21st Saudi Computer Society National Computer Conference (NCC), Riyadh, Saudi Arabia.","DOI":"10.1109\/NCG.2018.8592999"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"102394","DOI":"10.1016\/j.scs.2020.102394","article-title":"Trustworthy and sustainable smart city services at the edge","volume":"62","author":"Jararweh","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Barth\u00e9lemy, J., Verstaevel, N., Forehead, H., and Perez, P. (2019). Edge-computing video analytics for real-time traffic monitoring in a smart city. Sensors, 19.","DOI":"10.3390\/s19092048"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.future.2017.05.034","article-title":"An edge-based platform for dynamic Smart City applications","volume":"76","author":"Cicirelli","year":"2017","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1109\/MCOM.2017.1600249CM","article-title":"Mobile edge computing potential in making cities smarter","volume":"55","author":"Taleb","year":"2017","journal-title":"IEEE Commun. Mag."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Giordano, A., Spezzano, G., and Vinci, A. (2016, January 15\u201317). Smart agents and fog computing for smart city applications. Proceedings of the International Conference on Smart Cities, Malaga, Spain.","DOI":"10.1007\/978-3-319-39595-1_14"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"14410","DOI":"10.1109\/ACCESS.2019.2893486","article-title":"Task scheduling for smart city applications based on multi-server mobile edge computing","volume":"7","author":"Deng","year":"2019","journal-title":"IEEE Access"},{"key":"ref_15","unstructured":"Chiang, M., and Shi, W. (2017). Grand Challenges in Edge Computing, Technical Report."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1109\/JIOT.2016.2579198","article-title":"Edge Computing: Vision and Challenges","volume":"3","author":"Shi","year":"2016","journal-title":"IEEE Internet Things J."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1093\/cjres\/rsu027","article-title":"Making sense of smart cities: Addressing present shortcomings","volume":"8","author":"Kitchin","year":"2015","journal-title":"Camb. J. Reg. Econ. Soc."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1109\/MCOM.2017.1700246","article-title":"Software-defined networks with mobile edge computing and caching for smart cities: A big data deep reinforcement learning approach","volume":"55","author":"He","year":"2017","journal-title":"IEEE Commun. Mag."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"9073","DOI":"10.1109\/TVT.2018.2865211","article-title":"Delay-tolerant data traffic to software-defined vehicular networks with mobile edge computing in smart city","volume":"67","author":"Li","year":"2018","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_20","unstructured":"Lov\u00e9n, L., Lepp\u00e4nen, T., Peltonen, E., Partala, J., Harjula, E., Porambage, P., Ylianttila, M., and Riekki, J. (2019, January 24\u201326). EdgeAI: A vision for distributed, edge-native artificial intelligence in future 6G networks. Proceedings of the 1st 6G Wireless Summit, Levi, Finland."},{"key":"ref_21","unstructured":"Partala, J., Lov\u00e9n, L., Peltonen, E., Porambage, P., Ylianttila, M., and Sepp\u00e4nen, T. (2019, January 1\u20134). EdgeAI: A vision for privacy-preserving machine learning on the edge. Proceedings of the 10th Nordic Workshop on System and Network Optimization for Wireless (SNOW), Ruka, Finland."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2204","DOI":"10.1109\/JPROC.2019.2941458","article-title":"Wireless network intelligence at the edge","volume":"107","author":"Park","year":"2019","journal-title":"Proc. IEEE"},{"key":"ref_23","first-page":"1","article-title":"Mobile road weather sensor calibration by sensor fusion and linear mixed models","volume":"14","author":"Karsisto","year":"2019","journal-title":"PLoS ONE"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Rasmussen, C.E., and Williams, C.K. (2006). Gaussian Processes for Machine Learning, The MIT Press.","DOI":"10.7551\/mitpress\/3206.001.0001"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Lov\u00e9n, L., Peltonen, E., Pandya, A., Lepp\u00e4nen, T., Gilman, E., Pirttikangas, S., and Riekki, J. (August, January 29). Towards EDISON: An edge-native approach to distributed interpolation of environmental data. Proceedings of the 28th International Conference on Computer Communications and Networks (ICCCN2019), 1st Edge of Things Workshop 2019 (EoT2019), Valencia, Spain.","DOI":"10.1109\/ICCCN.2019.8847121"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Iorga, M., Feldman, L., Barton, R., Martin, M.J., Goren, N., and Mahmoudi, C. (2018). Fog Computing Conceptual Model, Technical Report.","DOI":"10.6028\/NIST.SP.500-325"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/j.tele.2014.09.004","article-title":"Mobile city applications for Brussels citizens: Smart City trends, challenges and a reality check","volume":"32","author":"Walravens","year":"2015","journal-title":"Telemat. Inform."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3124391","article-title":"Software platforms for smart cities: Concepts, requirements, challenges, and a unified reference architecture","volume":"50","author":"Santana","year":"2016","journal-title":"ACM Comput. Surv."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Mehmood, H., Gilman, E., and Cortes, M. (2019, January 8\u201312). Implementing big data lake for heterogeneous data sources. Proceedings of the 1st International Workshop on Data-Driven Smart Cities, in Conjunction with 35th IEEE International Conference on Data Engineering (ICDE 2019), Macao, China.","DOI":"10.1109\/ICDEW.2019.00-37"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Raza, U., Camerra, A., Murphy, A.L., Palpanas, T., and Picco, G.P. (2012, January 19\u201323). What does model-driven data acquisition really achieve in wireless sensor networks?. Proceedings of the 2012 IEEE International Conference on Pervasive Computing and Communications, PerCom 2012, Lugano, Switzerland.","DOI":"10.1109\/PerCom.2012.6199853"},{"key":"ref_31","unstructured":"Peltonen, E., Lepp\u00e4nen, T., and Lov\u00e9n, L. (2019, January 24\u201326). EdgeAI: Edge-native distributed platform for artificial intelligence. Proceedings of the 1st 6G Wireless Summit, Levi, Finland."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1016\/j.jpdc.2018.08.009","article-title":"Edge computing framework for enabling situation awareness in IoT based smart city","volume":"122","author":"Hossain","year":"2018","journal-title":"J. Parallel Distrib. Comput."},{"key":"ref_33","unstructured":"Fortino, G., Russo, W., Savaglio, C., Viroli, M., and Zhou, M. (2017, January 15\u201317). Modeling opportunistic IoT services in open IoT ecosystems. Proceedings of the XVIII Workshop \u201cFrom Objects to Agents\u201d, Scilla, Italy."},{"key":"ref_34","first-page":"242","article-title":"Cloud-SEnergy: A bin-packing based multi-cloud service broker for energy efficient composition and execution of data-intensive applications","volume":"19","author":"Baker","year":"2018","journal-title":"Sustain. Comput. Inform. Syst."},{"key":"ref_35","unstructured":"Lagerspetz, E., Varjonen, S., Concas, F., Mineraud, J., and Tarkoma, S. (November, January 29). Demo: MegaSense: Megacity-scale accurate air quality sensing with the edge. Proceedings of the 24th Annual International Conference on Mobile Computing and Networking (MobiCom \u201918), New Delhi, India."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"778","DOI":"10.1007\/s10489-019-01549-7","article-title":"Cluster-based kriging approximation algorithms for complexity reduction","volume":"50","author":"Wang","year":"2020","journal-title":"Appl. Intell."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-020-79148-7","article-title":"A novel framework for spatio-temporal prediction of environmental data using deep learning","volume":"10","author":"Amato","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_38","first-page":"1","article-title":"Patchwork kriging for large-scale Gaussian process regression","volume":"19","author":"Park","year":"2018","journal-title":"J. Mach. Learn. Res."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Yasojima, C., Prot\u00e1zio, J., Meiguins, B., Neto, N., and Morais, J. (2019). A new methodology for automatic cluster-based kriging using K-nearest neighbor and genetic algorithms. Information, 10.","DOI":"10.3390\/info10110357"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Hern\u00e1ndez-Pe\u00f1aloza, G., and Beferull-Lozano, B. (2012, January 10\u201315). Field estimation in wireless sensor networks using distributed kriging. Proceedings of the IEEE International Conference on Communications, Ottawa, ON, Canada.","DOI":"10.1109\/ICC.2012.6364464"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Chowdappa, V.P., Botella, C., and Beferull-Lozano, B. (2015). Distributed clustering algorithm for spatial field reconstruction in wireless sensor networks. IEEE Veh. Technol. Conf., 2015.","DOI":"10.1109\/VTCSpring.2015.7145783"},{"key":"ref_42","unstructured":"Park, J., Wang, S., Elgabli, A., Oh, S., Jeong, E., Cha, H., Kim, H., Kim, S.L., and Bennis, M. (2019). Distilling on-device intelligence at the network edge. arXiv."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"7457","DOI":"10.1109\/JIOT.2020.2984887","article-title":"Edge intelligence: The confluence of edge computing and artificial intelligence","volume":"7","author":"Deng","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_44","unstructured":"Xu, D., Li, T., Li, Y., Su, X., Tarkoma, S., and Hui, P. (2020). A survey on edge intelligence. arXiv."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Zhou, Z., Chen, X., Li, E., Zeng, L., Luo, K., and Zhang, J. (2019). Edge intelligence: Paving the last mile of artificial intelligence with edge computing. Proc. IEEE, 107.","DOI":"10.1109\/JPROC.2019.2918951"},{"key":"ref_46","unstructured":"Jeong, E., Oh, S., Kim, H., Park, J., Bennis, M., and Kim, S.L. (2018). Communication-efficient on-device machine learning: Federated distillation and augmentation under non-iid private data. arXiv."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3339474","article-title":"Federated machine learning: Concept and applications","volume":"10","author":"Yang","year":"2019","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"234","DOI":"10.2307\/143141","article-title":"A Computer Movie Simulating Urban Growth in the Detroit Region","volume":"46","author":"Tobler","year":"1970","journal-title":"Econ. Geogr."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"L\u00e4hderanta, T., Lepp\u00e4nen, T., Ruha, L., Lov\u00e9n, L., Harjula, E., Ylianttila, M., Riekki, J., and Sillanp\u00e4\u00e4, M.J. (2021). Edge computing server placement with capacitated location allocation. J. Parallel Distrib. Comput., in press.","DOI":"10.1016\/j.jpdc.2021.03.007"},{"key":"ref_50","unstructured":"Ruha, L., L\u00e4hderanta, T., Lov\u00e9n, L., Kuismin, M., Lepp\u00e4nen, T., Riekki, J., and Sillanp\u00e4\u00e4, M.J. (2020). Capacitated spatial clustering with multiple constraints and attributes. arXiv."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Lov\u00e9n, L., L\u00e4hderanta, T., Ruha, L., Lepp\u00e4nen, T., Peltonen, E., Riekki, J., and Sillanp\u00e4\u00e4, M.J. (2020, January 23\u201327). Scaling up an Edge Server Deployment. Proceedings of the 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), online.","DOI":"10.1109\/PerComWorkshops48775.2020.9156204"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Fix, E., and Hodges, J.L. (1951). Discriminatory Analysis. Nonparametric Discrimination: Consistency Properties, USAF School of Aviation Medicine. Technical Report.","DOI":"10.1037\/e471672008-001"},{"key":"ref_53","unstructured":"Nychka, D., Furrer, R., Paige, J., and Sain, S. (2021, March 23). Fields: Tools for Spatial Data. R Package Version 11.6; CRAN. Available online: https:\/\/cran.r-project.org\/web\/packages\/fields\/index.html."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.enbuild.2013.04.014","article-title":"Investigation of urban microclimate parameters in an urban center","volume":"64","author":"Dimoudi","year":"2013","journal-title":"Energy Build."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"McLean, D.J., and Volponi, M.A.S. (2018). trajr: An R package for characterisation of animal trajectories. Ethology, 124.","DOI":"10.1111\/eth.12739"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1016\/j.cageo.2004.03.012","article-title":"Multivariable geostatistics in S: The gstat package","volume":"30","author":"Pebesma","year":"2004","journal-title":"Comput. Geosci."},{"key":"ref_57","first-page":"204","article-title":"Spatio-Temporal Interpolation using gstat","volume":"8","author":"Pebesma","year":"2016","journal-title":"RFID J."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v051.i07","article-title":"Spacetime: Spatio-Temporal Data in R","volume":"51","author":"Pebesma","year":"2012","journal-title":"J. Stat. Softw."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Bivand, R.S., Pebesma, E., and Gomez-Rubio, V. (2013). Applied Spatial Data Analysis with R, Springer. [2nd ed.].","DOI":"10.1007\/978-1-4614-7618-4"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"223418","DOI":"10.1109\/ACCESS.2020.3041765","article-title":"Machine Learning Meets Communication Networks: Current Trends and Future Challenges","volume":"8","author":"Ahmad","year":"2020","journal-title":"IEEE Access"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1175\/WAF-D-18-0167.1","article-title":"Verification of road surface temperature forecasts assimilating data from mobile sensors","volume":"34","author":"Karsisto","year":"2019","journal-title":"Weather Forecast."},{"key":"ref_62","unstructured":"Lov\u00e9n, L., Gilman, E., Riekki, J., L\u00e4\u00e4r\u00e4, E., Sukuvaara, T., M\u00e4enp\u00e4\u00e4, K., Sillanp\u00e4\u00e4, M.J., and Pirttikangas, S. (2017, January 7\u20138). Pilot study: Road\u2013tyre friction prediction by statistical methods and data fusion. In Proceedings of the 2017 International Workshop on Smart Sensing System (IWSSS17), Oulu, Finland."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/7\/2279\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:40:35Z","timestamp":1760161235000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/7\/2279"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,24]]},"references-count":62,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2021,4]]}},"alternative-id":["s21072279"],"URL":"https:\/\/doi.org\/10.3390\/s21072279","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,3,24]]}}}