{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T07:46:39Z","timestamp":1769672799968,"version":"3.49.0"},"reference-count":43,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,11,8]],"date-time":"2022-11-08T00:00:00Z","timestamp":1667865600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"PDR2020","award":["PDR2020-101-031358"],"award-info":[{"award-number":["PDR2020-101-031358"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Within the scope of precision agriculture, many applications have been developed to support decision making and yield enhancement. Fruit detection has attracted considerable attention from researchers, and it can be used offline. In contrast, some applications, such as robot vision in orchards, require computer vision models to run on edge devices while performing inferences at high speed. In this area, most modern applications use an integrated graphics processing unit (GPU). In this work, we propose the use of a tensor processing unit (TPU) accelerator with a Raspberry Pi target device and the state-of-the-art, lightweight, and hardware-aware MobileDet detector model. Our contribution is the extension of the possibilities of using accelerators (the TPU) for edge devices in precision agriculture. The proposed method was evaluated using a novel dataset of peaches with three cultivars, which will be made available for further studies. The model achieved an average precision (AP) of 88.2% and a performance of 19.84 frames per second (FPS) at an image size of 640 \u00d7 480. The results obtained show that the TPU accelerator can be an excellent alternative for processing on the edge in precision agriculture.<\/jats:p>","DOI":"10.3390\/fi14110323","type":"journal-article","created":{"date-parts":[[2022,11,8]],"date-time":"2022-11-08T10:53:06Z","timestamp":1667904786000},"page":"323","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Real-Time Image Detection for Edge Devices: A Peach Fruit Detection Application"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6027-7763","authenticated-orcid":false,"given":"Eduardo","family":"Assun\u00e7\u00e3o","sequence":"first","affiliation":[{"name":"C-MAST Center for Mechanical and Aerospace Science and Technologies, University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"},{"name":"Instituto de Telecomunica\u00e7\u00f5es, University of Beira Interior, Rua Marqu\u00eas d\u2019\u00c1vila e Bolama, 6201-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1691-1709","authenticated-orcid":false,"given":"Pedro D.","family":"Gaspar","sequence":"additional","affiliation":[{"name":"C-MAST Center for Mechanical and Aerospace Science and Technologies, University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"},{"name":"Department of Electromechanical Engineering, University of Beira Interior, Rua Marqu\u00eas d\u2019\u00c1vila e Bolama, 6201-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2319-8211","authenticated-orcid":false,"given":"Khadijeh","family":"Alibabaei","sequence":"additional","affiliation":[{"name":"C-MAST Center for Mechanical and Aerospace Science and Technologies, University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"},{"name":"Department of Electromechanical Engineering, University of Beira Interior, Rua Marqu\u00eas d\u2019\u00c1vila e Bolama, 6201-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6599-0688","authenticated-orcid":false,"given":"Maria P.","family":"Sim\u00f5es","sequence":"additional","affiliation":[{"name":"Polytechnic Institute of Castelo Branco, Av. Pedro \u00c1lvares Cabral n\u00ba 12, 6000-084 Castelo Branco, Portugal"},{"name":"CERNAS, Research Center for Natural Resources, Environment and Society, Escola Superiora Agr\u00e1ria de Coimbra Bencanta, 3045-601 Coimbra, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2551-8570","authenticated-orcid":false,"given":"Hugo","family":"Proen\u00e7a","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es, University of Beira Interior, Rua Marqu\u00eas d\u2019\u00c1vila e Bolama, 6201-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8057-5474","authenticated-orcid":false,"given":"Vasco N. G. J.","family":"Soares","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es, University of Beira Interior, Rua Marqu\u00eas d\u2019\u00c1vila e Bolama, 6201-001 Covilh\u00e3, Portugal"},{"name":"Polytechnic Institute of Castelo Branco, Av. Pedro \u00c1lvares Cabral n\u00ba 12, 6000-084 Castelo Branco, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5830-3790","authenticated-orcid":false,"given":"Jo\u00e3o M. L. P.","family":"Caldeira","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es, University of Beira Interior, Rua Marqu\u00eas d\u2019\u00c1vila e Bolama, 6201-001 Covilh\u00e3, Portugal"},{"name":"Polytechnic Institute of Castelo Branco, Av. Pedro \u00c1lvares Cabral n\u00ba 12, 6000-084 Castelo Branco, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Roy, P., Kislay, A., Plonski, P.A., Luby, J., and Isler, V. (2019). Vision-based preharvest yield mapping for apple orchards. Comput. Electron. Agric., 164.","DOI":"10.1016\/j.compag.2019.104897"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Assun\u00e7\u00e3o, E., Diniz, C., Gaspar, P.D., and Proen\u00e7a, H. 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