AntPi: A Raspberry Pi based edge–cloud system for real-time ant species detection using YOLO Article Swipe
Lorenzo Palazzetti
,
Daniele Giannetti
,
Antonio Verolino
,
Donató A. Grasso
,
Cristina M. Pinotti
,
Francesco Betti Sorbelli
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.ecoinf.2025.103383
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.ecoinf.2025.103383
Ant detection is essential for ecological research, offering insights into biodiversity, habitat health, and environmental change. Traditional detection techniques rely on manual sampling methods, which are labor-intensive and time-consuming. Recent advances in autonomous, vision based systems show promise for insect monitoring, yet no dedicated, field ready solution exists for ant identification. In this work, we present AntPi, a deep learning based system for real-time detection and classification on a Linux development board. To the best of our knowledge, the system is trained on the first dedicated dataset for arboricolous ants, comprising five species and one morphotype, sourced from citizen science contributions and direct field captures. Our approach employs the “You Only Look Once” (YOLO) framework for efficient object detection, augmented with environmental sensors to enable correlation between climatic variables and ant activity. To evaluate performance and robustness, we compare AntPi with an alternative configuration, including controlled experiments using background-only images with artificial ant-like noise, and introduce a novel robustness indicator to assess reliability under realistic conditions. Experimental results demonstrate strong detection performance and confirm the feasibility of automated, in-field ant monitoring.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.ecoinf.2025.103383
- OA Status
- gold
- Cited By
- 1
- References
- 62
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4413274899Canonical identifier for this work in OpenAlex
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https://doi.org/10.1016/j.ecoinf.2025.103383Digital Object Identifier
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AntPi: A Raspberry Pi based edge–cloud system for real-time ant species detection using YOLOWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
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2025-08-18Full publication date if available
- Authors
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Lorenzo Palazzetti, Daniele Giannetti, Antonio Verolino, Donató A. Grasso, Cristina M. Pinotti, Francesco Betti SorbelliList of authors in order
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https://doi.org/10.1016/j.ecoinf.2025.103383Publisher landing page
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goldOpen access status per OpenAlex
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https://doi.org/10.1016/j.ecoinf.2025.103383Direct OA link when available
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Raspberry pi, Cloud computing, ANT, Blowing a raspberry, Enhanced Data Rates for GSM Evolution, Computer science, Remote sensing, Biology, Ecology, Artificial intelligence, Geography, Horticulture, Embedded system, Operating system, Internet of ThingsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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-
10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W6838401136, https://openalex.org/W4404284452, https://openalex.org/W4398221043, https://openalex.org/W6857220164, https://openalex.org/W4401379833, https://openalex.org/W4403674852, https://openalex.org/W4404065244, https://openalex.org/W4386647973, https://openalex.org/W6874757748, https://openalex.org/W4324342085, https://openalex.org/W4409540210, https://openalex.org/W4403962137, https://openalex.org/W6604653223, https://openalex.org/W2623397520, https://openalex.org/W3115828675, https://openalex.org/W4407806830, https://openalex.org/W4281490360, https://openalex.org/W4225714398, https://openalex.org/W4288758450, https://openalex.org/W2104914796, https://openalex.org/W4392094225, https://openalex.org/W2887996679, https://openalex.org/W6864593018, https://openalex.org/W2985233588, https://openalex.org/W4313906971, https://openalex.org/W2120137198, https://openalex.org/W4401305620, https://openalex.org/W4395479439, https://openalex.org/W4391756450, https://openalex.org/W6878753206, https://openalex.org/W2900457482, https://openalex.org/W6869091067, https://openalex.org/W6788020608, https://openalex.org/W1995081477, https://openalex.org/W4401894784, https://openalex.org/W3206493388, https://openalex.org/W4379364715, https://openalex.org/W3086844398, https://openalex.org/W4220852560, https://openalex.org/W3006495771, https://openalex.org/W4387711020, https://openalex.org/W4393900580, https://openalex.org/W4404283459, https://openalex.org/W4400369419, https://openalex.org/W6862000706, https://openalex.org/W4304689616, https://openalex.org/W6689694917, https://openalex.org/W4313907040, https://openalex.org/W4404985384, https://openalex.org/W4400490830, https://openalex.org/W4404314259, https://openalex.org/W4404303854, https://openalex.org/W4399548851, https://openalex.org/W1861492603, https://openalex.org/W4398810114, https://openalex.org/W3118611023, https://openalex.org/W4249254020, https://openalex.org/W4403897037, https://openalex.org/W3159179906, https://openalex.org/W3109831909, https://openalex.org/W4282974753, https://openalex.org/W4249502209 |
| referenced_works_count | 62 |
| abstract_inverted_index.a | 57, 68, 156 |
| abstract_inverted_index.In | 51 |
| abstract_inverted_index.To | 72, 132 |
| abstract_inverted_index.an | 141 |
| abstract_inverted_index.in | 31 |
| abstract_inverted_index.is | 2, 80 |
| abstract_inverted_index.no | 42 |
| abstract_inverted_index.of | 75, 176 |
| abstract_inverted_index.on | 20, 67, 82 |
| abstract_inverted_index.to | 123, 160 |
| abstract_inverted_index.we | 54, 137 |
| abstract_inverted_index.Ant | 0 |
| abstract_inverted_index.Our | 105 |
| abstract_inverted_index.and | 13, 27, 65, 93, 101, 129, 135, 154, 172 |
| abstract_inverted_index.ant | 49, 130, 179 |
| abstract_inverted_index.are | 25 |
| abstract_inverted_index.for | 4, 38, 48, 62, 87, 115 |
| abstract_inverted_index.one | 94 |
| abstract_inverted_index.our | 76 |
| abstract_inverted_index.the | 73, 78, 83, 108, 174 |
| abstract_inverted_index.yet | 41 |
| abstract_inverted_index.Look | 111 |
| abstract_inverted_index.Only | 110 |
| abstract_inverted_index.best | 74 |
| abstract_inverted_index.deep | 58 |
| abstract_inverted_index.five | 91 |
| abstract_inverted_index.from | 97 |
| abstract_inverted_index.into | 9 |
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| abstract_inverted_index.show | 36 |
| abstract_inverted_index.this | 52 |
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| abstract_inverted_index.AntPi | 139 |
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| abstract_inverted_index.ants, | 89 |
| abstract_inverted_index.based | 34, 60 |
| abstract_inverted_index.field | 44, 103 |
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| abstract_inverted_index.novel | 157 |
| abstract_inverted_index.ready | 45 |
| abstract_inverted_index.under | 163 |
| abstract_inverted_index.using | 147 |
| abstract_inverted_index.which | 24 |
| abstract_inverted_index.work, | 53 |
| abstract_inverted_index.(YOLO) | 113 |
| abstract_inverted_index.AntPi, | 56 |
| abstract_inverted_index.Recent | 29 |
| abstract_inverted_index.assess | 161 |
| abstract_inverted_index.board. | 71 |
| abstract_inverted_index.direct | 102 |
| abstract_inverted_index.enable | 124 |
| abstract_inverted_index.exists | 47 |
| abstract_inverted_index.images | 149 |
| abstract_inverted_index.insect | 39 |
| abstract_inverted_index.manual | 21 |
| abstract_inverted_index.noise, | 153 |
| abstract_inverted_index.object | 117 |
| abstract_inverted_index.strong | 169 |
| abstract_inverted_index.system | 61, 79 |
| abstract_inverted_index.vision | 33 |
| abstract_inverted_index.“You | 109 |
| abstract_inverted_index.Once” | 112 |
| abstract_inverted_index.between | 126 |
| abstract_inverted_index.change. | 15 |
| abstract_inverted_index.citizen | 98 |
| abstract_inverted_index.compare | 138 |
| abstract_inverted_index.confirm | 173 |
| abstract_inverted_index.dataset | 86 |
| abstract_inverted_index.employs | 107 |
| abstract_inverted_index.habitat | 11 |
| abstract_inverted_index.health, | 12 |
| abstract_inverted_index.present | 55 |
| abstract_inverted_index.promise | 37 |
| abstract_inverted_index.results | 167 |
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| abstract_inverted_index.sensors | 122 |
| abstract_inverted_index.sourced | 96 |
| abstract_inverted_index.species | 92 |
| abstract_inverted_index.systems | 35 |
| abstract_inverted_index.trained | 81 |
| abstract_inverted_index.advances | 30 |
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| abstract_inverted_index.in-field | 178 |
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| abstract_inverted_index.learning | 59 |
| abstract_inverted_index.methods, | 23 |
| abstract_inverted_index.offering | 7 |
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| abstract_inverted_index.solution | 46 |
| abstract_inverted_index.activity. | 131 |
| abstract_inverted_index.augmented | 119 |
| abstract_inverted_index.captures. | 104 |
| abstract_inverted_index.dedicated | 85 |
| abstract_inverted_index.detection | 1, 17, 64, 170 |
| abstract_inverted_index.efficient | 116 |
| abstract_inverted_index.essential | 3 |
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| abstract_inverted_index.including | 144 |
| abstract_inverted_index.indicator | 159 |
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| abstract_inverted_index.real-time | 63 |
| abstract_inverted_index.realistic | 164 |
| abstract_inverted_index.research, | 6 |
| abstract_inverted_index.variables | 128 |
| abstract_inverted_index.artificial | 151 |
| abstract_inverted_index.automated, | 177 |
| abstract_inverted_index.comprising | 90 |
| abstract_inverted_index.controlled | 145 |
| abstract_inverted_index.dedicated, | 43 |
| abstract_inverted_index.detection, | 118 |
| abstract_inverted_index.ecological | 5 |
| abstract_inverted_index.knowledge, | 77 |
| abstract_inverted_index.robustness | 158 |
| abstract_inverted_index.techniques | 18 |
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| abstract_inverted_index.experiments | 146 |
| abstract_inverted_index.feasibility | 175 |
| abstract_inverted_index.monitoring, | 40 |
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| abstract_inverted_index.morphotype, | 95 |
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| abstract_inverted_index.robustness, | 136 |
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| abstract_inverted_index.biodiversity, | 10 |
| abstract_inverted_index.contributions | 100 |
| abstract_inverted_index.environmental | 14, 121 |
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| abstract_inverted_index.configuration, | 143 |
| abstract_inverted_index.background-only | 148 |
| abstract_inverted_index.identification. | 50 |
| abstract_inverted_index.labor-intensive | 26 |
| abstract_inverted_index.time-consuming. | 28 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.91677692 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |