{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T23:22:40Z","timestamp":1775604160685,"version":"3.50.1"},"reference-count":31,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,6,25]],"date-time":"2020-06-25T00:00:00Z","timestamp":1593043200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Italian Ministry of Education, University and Research","award":["\"Departments of Excellence-2018\" Program, DIBAF-Department of University of 422 Tuscia, Project \u201dLandscape 4.0 \u2013 food, wellbeing and environment\u201d"],"award-info":[{"award-number":["\"Departments of Excellence-2018\" Program, DIBAF-Department of University of 422 Tuscia, Project \u201dLandscape 4.0 \u2013 food, wellbeing and environment\u201d"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Monitoring streamflow velocity is of paramount importance for water resources management and in engineering practice. To this aim, image-based approaches have proved to be reliable systems to non-intrusively monitor water bodies in remote places at variable flow regimes. Nonetheless, to tackle their computational and energy requirements, offload processing and high-speed internet connections in the monitored environments, which are often difficult to access, is mandatory hence limiting the effective deployment of such techniques in several relevant circumstances. In this paper, we advance and simplify streamflow velocity monitoring by directly processing the image stream in situ with a low-power embedded system. By leveraging its standard parallel processing capability and exploiting functional simplifications, we achieve an accuracy comparable to state-of-the-art algorithms that typically require expensive computing devices and infrastructures. The advantage of monitoring streamflow velocity in situ with a lightweight and cost-effective embedded processing device is threefold. First, it circumvents the need for wideband internet connections, which are expensive and impractical in remote environments. Second, it massively reduces the overall energy consumption, bandwidth and deployment cost. Third, when monitoring more than one river section, processing \u201cat the very edge\u201d of the system efficiency improves scalability by a large margin, compared to offload solutions based on remote or cloud processing. Therefore, enabling streamflow velocity monitoring in situ with low-cost embedded devices would foster the widespread diffusion of gauge cameras even in developing countries where appropriate infrastructure might be not available or too expensive.<\/jats:p>","DOI":"10.3390\/rs12122047","type":"journal-article","created":{"date-parts":[[2020,6,25]],"date-time":"2020-06-25T10:36:54Z","timestamp":1593081414000},"page":"2047","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Enabling Image-Based Streamflow Monitoring at the Edge"],"prefix":"10.3390","volume":"12","author":[{"given":"Fabio","family":"Tosi","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, University of Bologna, 40136 Bologna, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matteo","family":"Rocca","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Bologna, 40136 Bologna, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Filippo","family":"Aleotti","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Bologna, 40136 Bologna, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matteo","family":"Poggi","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Bologna, 40136 Bologna, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3681-7704","authenticated-orcid":false,"given":"Stefano","family":"Mattoccia","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Bologna, 40136 Bologna, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5176-3492","authenticated-orcid":false,"given":"Flavia","family":"Tauro","sequence":"additional","affiliation":[{"name":"Department for Innovation in Biological, Agro-food and Forest Systems, University of Tuscia, 01100 Viterbo, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9652-7901","authenticated-orcid":false,"given":"Elena","family":"Toth","sequence":"additional","affiliation":[{"name":"Department of Civil, Chemical, Environmental, and Materials Engineering, University of Bologna, 40136 Bologna, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Salvatore","family":"Grimaldi","sequence":"additional","affiliation":[{"name":"Department for Innovation in Biological, Agro-food and Forest Systems, University of Tuscia, 01100 Viterbo, Italy"},{"name":"Department of Mechanical and Aerospace Engineering, Tandon School of Engineering, New York University, Brooklyn, NY 10003, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1314","DOI":"10.1080\/02626667.2011.607822","article-title":"Experimental methods for river discharge measurements: Comparison among tracers and current meter","volume":"56","author":"Tazioli","year":"2011","journal-title":"Hydrol. Sci. J."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1080\/02626667.2017.1420191","article-title":"Measurements and Observations in the XXI century (MOXXI): Innovation and multidisciplinarity to sense the hydrological cycle","volume":"63","author":"Tauro","year":"2018","journal-title":"Hydrol. Sci. J."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1002\/wat2.1116","article-title":"Particle tracers and image analysis for surface flow observations","volume":"3","author":"Tauro","year":"2015","journal-title":"WIREs Water"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1080\/00221689809498626","article-title":"Large-scale particle image velocimetry for flow analysis in hydraulic engineering applications","volume":"36","author":"Fujita","year":"1997","journal-title":"J. Hydraul. Res."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1061\/(ASCE)1084-0699(2008)13:2(105)","article-title":"Experimental system for real-time discharge estimation using an image-based method","volume":"13","author":"Hauet","year":"2008","journal-title":"J. Hydrol. Eng."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"W09502","DOI":"10.1029\/2006WR005441","article-title":"Stream discharge using mobile large-scale particle image velocimetry: A proof of concept","volume":"44","author":"Kim","year":"2008","journal-title":"Water Resour. Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"241","DOI":"10.5194\/gi-5-241-2016","article-title":"A novel permanent gauge-cam station for surface-flow observations on the Tiber River","volume":"5","author":"Tauro","year":"2016","journal-title":"Geosci. Instrum. Methods Data Syst."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1002\/hyp.10532","article-title":"Gauging extreme floods on YouTube: Application of LSPIV to home movies for the post-event determination of stream discharges","volume":"30","author":"LeBoursicaud","year":"2015","journal-title":"Hydrol. Processes"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"766","DOI":"10.1016\/j.jhydrol.2016.07.036","article-title":"Crowdsourced data for flood hydrology: Feedback from recent citizen science projects in Argentina, France, and New Zealand","volume":"541","author":"LeCoz","year":"2016","journal-title":"J. Hydrol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"4005","DOI":"10.5194\/hess-20-4005-2016","article-title":"Technical Note: Advances in flash flood monitoring using unmanned aerial vehicles (UAVs)","volume":"20","author":"Perks","year":"2016","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"7977","DOI":"10.1002\/2015WR017783","article-title":"Resolving two-dimensional flow structure in rivers using large-scale particle image velocimetry: An example from a stream confluence","volume":"51","author":"Lewis","year":"2015","journal-title":"Water Resour. Res."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Pearce, S., Ljubi\u010di\u0107, R., Pe\u00f1a-Haro, S., Perks, M., Tauro, F., Pizarro, A., Dal Sasso, S.F., Strelnikova, D., Grimaldi, S., and Maddock, I. (2020). An Evaluation of Image Velocimetry Techniques under Low Flow Conditions and High Seeding Densities Using Unmanned Aerial Systems. Remote Sens., 12.","DOI":"10.5194\/egusphere-egu2020-324"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1146\/annurev.fl.23.010191.001401","article-title":"Particle-imaging techniques for experimental fluid-mechanics","volume":"23","author":"Adrian","year":"1991","journal-title":"Annu. Rev. Fluid Mech."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1007\/s00348-005-0991-7","article-title":"Twenty years of particle image velocimetry","volume":"39","author":"Adrian","year":"2005","journal-title":"Exp. Fluids"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Raffel, M., Willert, C.E., Wereley, S.T., and Kompenhans, J. (2007). Particle Image Velocimetry. A Practical Guide, Springer.","DOI":"10.1007\/978-3-540-72308-0"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"7470","DOI":"10.1002\/2014WR015952","article-title":"Orienting the camera and firing lasers to enhance large scale particle image velocimetry for streamflow monitoring","volume":"50","author":"Tauro","year":"2014","journal-title":"Water Resour. Res."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1080\/15715124.2007.9635310","article-title":"Development of a non-intrusive and efficient flow monitoring technique: The space-time image velocimetry (STIV)","volume":"5","author":"Fujita","year":"2007","journal-title":"Int. J. River Basin Manag."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1080\/00221689509498658","article-title":"Unsteady surface-velocity field measurement using particle tracking velocimetry","volume":"33","author":"Lloyd","year":"1995","journal-title":"J. Hydraul. Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1007\/s00348-010-0907-z","article-title":"Integrating cross-correlation and relaxation algorithms for particle tracking velocimetry","volume":"50","author":"Brevis","year":"2011","journal-title":"Exp. Fluids"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1007\/s10661-018-6848-3","article-title":"Exploring the optical experimental setup for surface flow velocity measurements using PTV","volume":"190","author":"DalSasso","year":"2018","journal-title":"Environ. Monitor. Assess."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"10374","DOI":"10.1002\/2017WR020848","article-title":"Streamflow observations from cameras: Large-scale particle image velocimetry or particle tracking velocimetry?","volume":"53","author":"Tauro","year":"2017","journal-title":"Water Resour. Res."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1016\/j.catena.2018.09.009","article-title":"PTV-Stream: A simplified particle tracking velocimetry framework for stream surface flow monitoring","volume":"172","author":"Tauro","year":"2019","journal-title":"Catena"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/0004-3702(81)90024-2","article-title":"Determining optical flow","volume":"17","author":"Horn","year":"1981","journal-title":"Artif. Intell."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.expthermflusci.2017.09.010","article-title":"Application of local opticl flow methods to high-velocity free-surface flows: Validation and application to stepped chutes","volume":"90","author":"Zhang","year":"2018","journal-title":"Exp. Therm. Fluid Sci."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Tauro, F., Tosi, F., Mattoccia, S., Toth, E., Piscopia, R., and Grimaldi, S. (2018). Optical Tracking Velocimetry (OTV): Leveraging Optical Flow and Trajectory-Based Filtering for Surface Streamflow Observations. Remote Sens., 10.","DOI":"10.3390\/rs10122010"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1109\/TPAMI.2008.275","article-title":"Faster and Better: A Machine Learning Approach to Corner Detection","volume":"32","author":"Rosten","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_27","unstructured":"Lucas, B.D., and Kanade, T. (1981, January 24\u201328). An Iterative Image Registration Technique with an Application to Stereo Vision. Proceedings of the 7th International Joint Conference on Artificial Intelligence, IJCAI \u201981, Vancouver, BC, Canada."},{"key":"ref_28","first-page":"120","article-title":"The OpenCV Library","volume":"25","author":"Bradski","year":"2000","journal-title":"Dr. Dobb\u2019s J."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Mitra, G., Johnston, B., Rendell, A.P., McCreath, E., and Zhou, J. (2013, January 20\u201324). Use of SIMD Vector Operations to Accelerate Application Code Performance on Low-Powered ARM and Intel Platforms. Proceedings of the 2013 IEEE 27th International Symposium on Parallel and Distributed Processing Workshops and PhD Forum, Cambridge, MA, USA. IPDPSW \u201913.","DOI":"10.1109\/IPDPSW.2013.207"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1109\/99.660313","article-title":"OpenMP: An Industry-Standard API for Shared-Memory Programming","volume":"5","author":"Dagum","year":"1998","journal-title":"IEEE Comput. Sci. Eng."},{"key":"ref_31","first-page":"298","article-title":"Intel\u00ae Threading Building Blocks","volume":"23","author":"Pheatt","year":"2008","journal-title":"J. Comput. Sci. Coll."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/12\/2047\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:42:49Z","timestamp":1760175769000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/12\/2047"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,25]]},"references-count":31,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2020,6]]}},"alternative-id":["rs12122047"],"URL":"https:\/\/doi.org\/10.3390\/rs12122047","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,25]]}}}