veterinaryВетеринария сегодняVeterinary Science Today2304-196X2658-6959"Veinard"10.29326/2304-196X-2025-14-2-123-132veterinary-909Research ArticleОБЗОРЫ | БОЛЕЗНИ СВИНЕЙREVIEWS | PORCINE DISEASESИнтеграция применения дронов и искусственного интеллекта для обнаружения диких кабанов, туш и их останков в связи с африканской чумой свинейArtificial intelligence-integrated drones used for detection of live wild boars, wild boar carcasses and remnants in the context of African swine fever controlhttps://orcid.org/0000-0002-0264-0218БеспаловаТ. Ю.BespalovaT. Yu.

Беспалова Татьяна Юрьевна, заместитель руководителя группы,

ул. Магнитогорская, 8, г. Самара, 443013.

Tatiana Yu. Bespalova, Deputy Head of Group, 

8, Magnitogorskaya str., Samara 443013.

27bt@mail.ruhttps://orcid.org/0000-0003-1079-6287КорогодинаЕ. В.KorogodinaЕ. V.

Корогодина Елена Владимировна, заместитель руководителя группы,

ул. Магнитогорская, 8, г. Самара, 443013.

Еlena V. Korogodina, Deputy Head of Group, 

8, Magnitogorskaya str., Samara 443013.

ElenaKorogodina@inbox.ruhttps://orcid.org/0000-0001-6411-6027МихалеваТ. В.MikhalevaT. V.

Михалева Татьяна Владимировна, канд. вет. наук, ученый секретарь, 

ул. Магнитогорская, 8, г. Самара, 443013.

Tatyana V. Mikhaleva, Cand. Sci. (Veterinary Medicine), Academic Secretary, 

8, Magnitogorskaya str., Samara 443013.

tatyanamihaleva@mail.ruФГБНУ «Федеральный исследовательский центр вирусологии и микробиологии» (ФГБНУ ФИЦВиМ); Самарский научно-исследовательский ветеринарный институт – филиал ФГБНУ ФИЦВиМ (СамНИВИ – филиал ФГБНУ ФИЦВиМ)РоссияFederal Research Center for Virology and Microbiology; Samara Research Veterinary Institute – Branch of Federal Research Center for Virology and MicrobiologyRussian Federation202528062025142123132Copyright © Беспалова Т.Ю., Корогодина Е.В., Михалева Т.В., 20252025Беспалова Т.Ю., Корогодина Е.В., Михалева Т.В.Bespalova T.Y., Korogodina Е.V., Mikhaleva T.V.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://veterinary.arriah.ru/jour/article/view/909Введение

Введение. Глобальное распространение африканской чумы свиней, смертельно опасного вирусного геморрагического заболевания домашних свиней и диких кабанов, диктует необходимость применения эффективных мер предупреждения и раннего выявления вспышек. Контроль численности популяции, а также поиск туш диких кабанов, погибших от африканской чумы свиней и являющихся источником передачи вируса, считаются приоритетными мерами в управлении заболеванием в дикой природе.

Цель исследования

Цель исследования. Обобщение имеющихся в настоящее время знаний о передовых технологиях применения беспилотных летательных аппаратов (дронов) в условиях дикой природы в сочетании с методами искусственного интеллекта.

Материалы и методы

Материалы и методы. При выполнении работы применялись аналитические методы исследований с использованием баз данных PubMed, Springer, Wiley Online Library, Google Scholar, CrossRef, РИНЦ, еLIBRARY, CyberLeninka.

Результаты

Результаты. В данном обзоре рассматривается возможность применения беспилотных летательных аппаратов (дронов) и искусственного интеллекта (нейронных сетей) для обнаружения диких кабанов и их останков в контексте борьбы с африканской чумой свиней. Подробно обсуждается роль диких кабанов в распространении заболевания и необходимость контроля их популяции, значение своевременного удаления трупов кабанов, при этом подчеркивается важность использования современных технологий для учета численности и плотности популяции дикого кабана. Проанализирована информация о применении дронов, оснащенных различными техническими средствами, при изучении популяций крупных видов животных в условиях дикой природы, отмечены преимущества и особенности использования беспилотных летательных аппаратов. Также обобщен опыт применения нейронных сетей в контексте автоматической обработки полученных с помощью дронов изображений животных.

Заключение

Заключение. Интеграция беспилотных летательных аппаратов и искусственного интеллекта, вероятно, может стать ключевым инструментом в контроле популяции дикого кабана и быстром обнаружении туш кабанов, погибших вследствие африканской чумы свиней, что в целом позволит повысить эффективность мер, направленных на борьбу с данным заболеванием.

Introduction

Introduction. Effective measures for African swine fever outbreak prevention and early detection are required in view of global spread of African swine fever, fatal viral hemorrhagic disease of domestic pigs and wild boars. Wild boar population managing and search for the wild boars died of African swine fever and being the virus source are considered priority measures for the disease control in wildlife.

Objective

Objective. Generalization of currently available knowledge about advanced technologies for the use of unmanned aerial vehicles (drones) in combination with artificial intelligence-based methods in the wild.

Materials and methods

Materials and methods. Analytical research methods including search in the following databases were used: PubMed, Springer, Wiley Online Library, Google Scholar, CrossRef, Russian Science Citation Index (RSCI), еLIBRARY, CyberLeninka.

Results

Results. Potential of using unmanned aerial vehicles (drones) and artificial intelligence (neural network) for detection of wild boars and their remnants in the context of combating African swine fever is described in the review. The role of wild boars in the disease spread and the need for wild boar population regulation are discussed in detail. Also, the importance of timely wild boar carcass removal and use of modern technologies for wild boar population recording and its density estimation are underlined. Data on the use of drones equipped with various technical devices for study of large animal populations in the wild are analyzed, advantages and peculiarities of unmanned aerial vehicle use are indicated. Experience gained in using neural networks-based techniques for automatic processing of animal images acquired from drones is also summarized.

Conclusion

Conclusion. Artificial intelligence-integrated unmanned aerial vehicles appear to be a key tool for managing wild boar populations and the rapid detection of African swine fever dead wild boars that allows improvement of overall effectiveness of the measures taken against this disease.

обзордикие кабаныафриканская чума свинейметоды учета животныхмониторингаэрофотосъемкабеспилотные летательные аппаратыдроныискусственный интеллектнейронная сетьreviewwild boarAfrican swine feveranimal recording techniquesmonitoringaerial photographyunmanned aerial vehiclesUAVsdronesartificial intelligenceneural networkРабота выполнена при поддержке Минобрнауки России в рамках Государственного задания ФГБНУ «Федеральный исследовательский центр вирусологии и микробиологии» (тема № FGNM-2022-0004). Авторы благодарят рецензентов за их вклад в экспертную оценку данной работы.The study was supported by the Ministry of Education and Science of the Russian Federation within the state assignment for the Federal Research Center for Virology and Microbiology (No. FGNM-2022-0004). The authors thank the reviewers for peer reviewing of this paper.ReferencesEFSA, Boklund A. E., Ståhl K., Miranda Chueca M. Á., Podgórski T., Vergne T., et al. Risk and protective factors for ASF in domestic pigs and wild boar in the EU, and mitigation measures for managing the disease in wild boar. EFSA Journal. 2024; 22 (12):e9095. https://doi.org/10.2903/j.efsa.2024.9095EFSA, Boklund A. E., Ståhl K., Miranda Chueca M. Á., Podgórski T., Vergne T., et al. Risk and protective factors for ASF in domestic pigs and wild boar in the EU, and mitigation measures for managing the disease in wild boar. EFSA Journal. 2024; 22 (12):e9095. https://doi.org/10.2903/j.efsa.2024.9095Pejsak Z., Truszczyński M., Niemczuk K., Kozak E., Markowska-Daniel I. Epidemiology of African swine fever in Poland since the detection of the first case. Polish Journal of Veterinary Sciences. 2014; 17 (4): 665–672. https://doi.org/10.2478/pjvs-2014-0097Pejsak Z., Truszczyński M., Niemczuk K., Kozak E., Markowska-Daniel I. Epidemiology of African swine fever in Poland since the detection of the first case. Polish Journal of Veterinary Sciences. 2014; 17 (4): 665–672. https://doi.org/10.2478/pjvs-2014-0097Oļševskis E., Guberti V., Seržants M., Westergaard J., Gallardo C., Rodze I., Depner K. African swine fever virus introduction into the EU in 2014: Experience of Latvia. Research in Veterinary Science. 2016; 105: 28–30. https://doi.org/10.1016/j.rvsc.2016.01.006Oļševskis E., Guberti V., Seržants M., Westergaard J., Gallardo C., Rodze I., Depner K. African swine fever virus introduction into the EU in 2014: Experience of Latvia. Research in Veterinary Science. 2016; 105: 28–30. https://doi.org/10.1016/j.rvsc.2016.01.006Nurmoja I., Schulz K., Staubach C., Sauter-Louis C., Depner K., Conraths F. J., Viltrop A. Development of African swine fever epidemic among wild boar in Estonia – two different areas in the epidemiological focus. Scientific Reports. 2017; 7:12562. https://doi.org/10.1038/s41598-017-12952-wNurmoja I., Schulz K., Staubach C., Sauter-Louis C., Depner K., Conraths F. J., Viltrop A. Development of African swine fever epidemic among wild boar in Estonia – two different areas in the epidemiological focus. Scientific Reports. 2017; 7:12562. https://doi.org/10.1038/s41598-017-12952-wSauter-Louis C., Forth J. H., Probst C., Staubach C., Hlinak A., Rudovsky A., et al. Joining the club: First detection of African swine fever in wild boar in Germany. Transboundary and Emerging Diseases. 2021; 68 (4): 1744–1752. https://doi.org/10.1111/tbed.13890Sauter-Louis C., Forth J. H., Probst C., Staubach C., Hlinak A., Rudovsky A., et al. Joining the club: First detection of African swine fever in wild boar in Germany. Transboundary and Emerging Diseases. 2021; 68 (4): 1744–1752. https://doi.org/10.1111/tbed.13890Sauter-Louis C., Conraths F. J., Probst C., Blohm U., Schulz K., Sehl J., et al. African swine fever in wild boar in Europe – A review. Viruses. 2021; 13 (9):1717. https://doi.org/10.3390/v13091717Sauter-Louis C., Conraths F. J., Probst C., Blohm U., Schulz K., Sehl J., et al. African swine fever in wild boar in Europe – A review. Viruses. 2021; 13 (9):1717. https://doi.org/10.3390/v13091717Chenais E., Ståhl K., Guberti V., Depner K. Identification of wild boar-habitat epidemiologic cycle in African swine fever epizootic. Emerging Infectious Diseases. 2018; 24 (4): 810–812. https://doi.org/10.3201/eid2404.172127Chenais E., Ståhl K., Guberti V., Depner K. Identification of wild boar-habitat epidemiologic cycle in African swine fever epizootic. Emerging Infectious Diseases. 2018; 24 (4): 810–812. https://doi.org/10.3201/eid2404.172127Probst C., Globig A., Knoll B., Conraths F. J., Depner K. Behaviour of free ranging wild boar towards their dead fellows: Potential implications for the transmission of African swine fever. Royal Society Open Science. 2017; 4 (5):170054. https://doi.org/10.1098/rsos.170054Probst C., Globig A., Knoll B., Conraths F. J., Depner K. Behaviour of free ranging wild boar towards their dead fellows: Potential implications for the transmission of African swine fever. Royal Society Open Science. 2017; 4 (5):170054. https://doi.org/10.1098/rsos.170054Fischer M., Hühr J., Blome S., Conraths F. J., Probst C. Stability of African swine fever virus in carcasses of domestic pigs and wild boar experimentally infected with the ASFV “Estonia 2014” isolate. Viruses. 2020; 12 (10):1118. https://doi.org/10.3390/v12101118Fischer M., Hühr J., Blome S., Conraths F. J., Probst C. Stability of African swine fever virus in carcasses of domestic pigs and wild boar experimentally infected with the ASFV “Estonia 2014” isolate. Viruses. 2020; 12 (10):1118. https://doi.org/10.3390/v12101118EFSA Panel on Animal Health and Welfare. Scientific opinion on African swine fever. EFSA Journal. 2015; 13 (7):4163. https://doi.org/10.2903/j.efsa.2015.4163EFSA Panel on Animal Health and Welfare. Scientific opinion on African swine fever. EFSA Journal. 2015; 13 (7):4163. https://doi.org/10.2903/j.efsa.2015.4163Gonzalez L. F., Montes G. A., Puig E., Johnson S., Mengersen K., Gaston K. J. Unmanned aerial vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation. Sensors. 2016; 16 (1):97. https://doi.org/10.3390/s16010097Gonzalez L. F., Montes G. A., Puig E., Johnson S., Mengersen K., Gaston K. J. Unmanned aerial vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation. Sensors. 2016; 16 (1):97. https://doi.org/10.3390/s16010097Schad L., Fischer J. Opportunities and risks in the use of drones for studying animal behavior. Methods in Ecology and Evolution. 2023; 14 (8): 1864–1872. https://doi.org/10.1111/2041-210x.13922Schad L., Fischer J. Opportunities and risks in the use of drones for studying animal behavior. Methods in Ecology and Evolution. 2023; 14 (8): 1864–1872. https://doi.org/10.1111/2041-210x.13922Petso T., Jamisola R. S. Jr. Wildlife conservation using drones and artificial intelligence in Africa. Science Robotics. 2023; 8 (85):eadm7008. https://doi.org/10.1126/scirobotics.adm7008Petso T., Jamisola R. S. Jr. Wildlife conservation using drones and artificial intelligence in Africa. Science Robotics. 2023; 8 (85):eadm7008. https://doi.org/10.1126/scirobotics.adm7008Hodgson J. C., Baylis S. M., Mott R., Herrod A., Clarke R. H. Precision wildlife monitoring using unmanned aerial vehicles. Scientific Reports. 2016; 6:22574. https://doi.org/10.1038/srep22574Hodgson J. C., Baylis S. M., Mott R., Herrod A., Clarke R. H. Precision wildlife monitoring using unmanned aerial vehicles. Scientific Reports. 2016; 6:22574. https://doi.org/10.1038/srep22574Marchowski D. Drones, automatic counting tools, and artificial neural networks in wildlife population censusing. Ecology and Evolution. 2021; 11 (22): 16214–16227. https://doi.org/10.1002/ece3.8302Marchowski D. Drones, automatic counting tools, and artificial neural networks in wildlife population censusing. Ecology and Evolution. 2021; 11 (22): 16214–16227. https://doi.org/10.1002/ece3.8302Demmer C. R., Demmer S., McIntyre T. Drones as a tool to study and monitor endangered grey crowned cranes (Balearica regulorum): Behavioural responses and recommended guidelines. Ecology and Evolution. 2024; 4 (2):e10990. https://doi.org/10.1002/ece3.10990Demmer C. R., Demmer S., McIntyre T. Drones as a tool to study and monitor endangered grey crowned cranes (Balearica regulorum): Behavioural responses and recommended guidelines. Ecology and Evolution. 2024; 4 (2):e10990. https://doi.org/10.1002/ece3.10990Lenzi J., Barnas A. F., ElSaid A. A., Desell T., Rockwell R. F., Ellis-Felege S. N. Artificial intelligence for automated detection of large mammals creates path to upscale drone surveys. Scientific Reports. 2023; 13:947. https://doi.org/10.1038/s41598-023-28240-9Lenzi J., Barnas A. F., ElSaid A. A., Desell T., Rockwell R. F., Ellis-Felege S. N. Artificial intelligence for automated detection of large mammals creates path to upscale drone surveys. Scientific Reports. 2023; 13:947. https://doi.org/10.1038/s41598-023-28240-9Brickson L., Zhang L., Vollrath F., Douglas-Hamilton I., Titus A. J. Elephants and algorithms: a review of the current and future role of AI in elephant monitoring. Journal of the Royal Society. 2023; 20 (208):20230367. https://doi.org/10.1098/rsif.2023.0367Brickson L., Zhang L., Vollrath F., Douglas-Hamilton I., Titus A. J. Elephants and algorithms: a review of the current and future role of AI in elephant monitoring. Journal of the Royal Society. 2023; 20 (208):20230367. https://doi.org/10.1098/rsif.2023.0367Witczuk J., Pagacz S., Zmarz A., Cypel M. Exploring the feasibility of unmanned aerial vehicles and thermal imaging for ungulate surveys in forests – preliminary results. International Journal of Remote Sensing. 2018; 39 (15–16): 5504–5521. http://doi.org/10.1080/01431161.2017.1390621Witczuk J., Pagacz S., Zmarz A., Cypel M. Exploring the feasibility of unmanned aerial vehicles and thermal imaging for ungulate surveys in forests – preliminary results. International Journal of Remote Sensing. 2018; 39 (15–16): 5504–5521. http://doi.org/10.1080/01431161.2017.1390621Linchant J., Lhoest S., Quevauvillers S., Lejeune P., Vermeulen C., Semeki Ngabinzeke J., et al. UAS imagery reveals new survey opportunities for counting hippos. PLoS ONE. 2018; 13 (11):e0206413. https://doi.org/10.1371/journal.pone.0206413Linchant J., Lhoest S., Quevauvillers S., Lejeune P., Vermeulen C., Semeki Ngabinzeke J., et al. UAS imagery reveals new survey opportunities for counting hippos. PLoS ONE. 2018; 13 (11):e0206413. https://doi.org/10.1371/journal.pone.0206413Semel B. P., Karpanty S. M., Vololonirina F. F., Rakotonanahary A. N. Eyes in the sky: Assessing the feasibility of low-cost, ready-to-use unmanned aerial vehicles to monitor primate populations directly. Folia Primatologica. 2019; 91 (1): 69–82. https://doi.org/10.1159/000496971Semel B. P., Karpanty S. M., Vololonirina F. F., Rakotonanahary A. N. Eyes in the sky: Assessing the feasibility of low-cost, ready-to-use unmanned aerial vehicles to monitor primate populations directly. Folia Primatologica. 2019; 91 (1): 69–82. https://doi.org/10.1159/000496971Baldwin R. W., Beaver J. T., Messinger M., Muday J., Windsor M., Larsen G. D., et al. Camera trap methods and drone thermal surveillance provide reliable, comparable density estimates of large, free-ranging ungulates. Animals. 2023; 13 (11):1884. https://doi.org/10.3390/ani13111884Baldwin R. W., Beaver J. T., Messinger M., Muday J., Windsor M., Larsen G. D., et al. Camera trap methods and drone thermal surveillance provide reliable, comparable density estimates of large, free-ranging ungulates. Animals. 2023; 13 (11):1884. https://doi.org/10.3390/ani13111884Krishnan B. S., Jones L. R., Elmore J. A., Samiappan S., Evans K. O., Pfeiffer M. B., et al. Fusion of visible and thermal images improves automated detection and classification of animals for drone surveys. Scientific Reports. 2023; 13:10385. https://doi.org/10.1038/s41598-023-37295-7Krishnan B. S., Jones L. R., Elmore J. A., Samiappan S., Evans K. O., Pfeiffer M. B., et al. Fusion of visible and thermal images improves automated detection and classification of animals for drone surveys. Scientific Reports. 2023; 13:10385. https://doi.org/10.1038/s41598-023-37295-7Corcoran E., Denman S., Hamilton G. Evaluating new technology for biodiversity monitoring: Are drone surveys biased? Ecology and Evolution. 2021; 11 (11): 6649–6656. https://doi.org/10.1002/ece3.7518Corcoran E., Denman S., Hamilton G. Evaluating new technology for biodiversity monitoring: Are drone surveys biased? Ecology and Evolution. 2021; 11 (11): 6649–6656. https://doi.org/10.1002/ece3.7518Hvala A., Rogers R. M., Alazab M., Campbell H. A. Supplementing aerial drone surveys with biotelemetry data validates wildlife detection probabilities. Frontiers in Conservation Science. 2023; 4:1203736. https://doi.org/10.3389/fcosc.2023.1203736Hvala A., Rogers R. M., Alazab M., Campbell H. A. Supplementing aerial drone surveys with biotelemetry data validates wildlife detection probabilities. Frontiers in Conservation Science. 2023; 4:1203736. https://doi.org/10.3389/fcosc.2023.1203736Tack J. Wild boar (Sus scrofa) populations in Europe: A scientific review of population trends and implications for management. Brussels: European Landowners’ Organization; 2018. 56 p. https://wildbeimwild.com/wp-content/uploads/2023/08/12-Tack-J-Wild-Boar-Population-Trends-inEurope-2018.pdfTack J. Wild boar (Sus scrofa) populations in Europe: A scientific review of population trends and implications for management. Brussels: European Landowners’ Organization; 2018. 56 p. https://wildbeimwild.com/wp-content/uploads/2023/08/12-Tack-J-Wild-Boar-Population-Trends-inEurope-2018.pdfCarpio A. J., Apollonio M., Acevedo P. Wild ungulate overabundance in Europe: contexts, causes, monitoring and management recommendations. Mammal Review. 2021; 51 (1): 95–108. https://doi.org/10.1111/mam.12221Carpio A. J., Apollonio M., Acevedo P. Wild ungulate overabundance in Europe: contexts, causes, monitoring and management recommendations. Mammal Review. 2021; 51 (1): 95–108. https://doi.org/10.1111/mam.12221Chenais E., Depner K., Guberti V., Dietze K., Viltrop A., Ståhl K. Epidemiological considerations on African swine fever in Europe 2014–2018. Porcine Health Management. 2019; 5:6. https://doi.org/10.1186/s40813018-0109-2Chenais E., Depner K., Guberti V., Dietze K., Viltrop A., Ståhl K. Epidemiological considerations on African swine fever in Europe 2014–2018. Porcine Health Management. 2019; 5:6. https://doi.org/10.1186/s40813018-0109-2Podgórski T., Borowik T., Łyjak M., Woźniakowski G. Spatial epidemiology of African swine fever: Host, landscape and anthropogenic drivers of disease occurrence in wild boar. Preventive Veterinary Medicine. 2020; 177:104691. https://doi.org/10.1016/j.prevetmed.2019.104691Podgórski T., Borowik T., Łyjak M., Woźniakowski G. Spatial epidemiology of African swine fever: Host, landscape and anthropogenic drivers of disease occurrence in wild boar. Preventive Veterinary Medicine. 2020; 177:104691. https://doi.org/10.1016/j.prevetmed.2019.104691Śmietanka K., Woźniakowski G., Kozak E., Niemczuk K., Frączyk M., Bocian Ł., et al. African swine fever epidemic, Poland, 2014–2015. Emerging Infectious Diseases. 2016; 22 (7): 1201–1207. https://doi.org/10.3201/eid2207.151708Śmietanka K., Woźniakowski G., Kozak E., Niemczuk K., Frączyk M., Bocian Ł., et al. African swine fever epidemic, Poland, 2014–2015. Emerging Infectious Diseases. 2016; 22 (7): 1201–1207. https://doi.org/10.3201/eid2207.151708Boklund A., Dhollander S., Chesnoiu Vasile T., Abrahantes J. C., Bøtner A., Gogin A., et al. Risk factors for African swine fever incursion in Romanian domestic farms during 2019. Scientific Reports. 2020; 10:10215. https://doi.org/10.1038/s41598-020-66381-3Boklund A., Dhollander S., Chesnoiu Vasile T., Abrahantes J. C., Bøtner A., Gogin A., et al. Risk factors for African swine fever incursion in Romanian domestic farms during 2019. Scientific Reports. 2020; 10:10215. https://doi.org/10.1038/s41598-020-66381-3Johann F., Handschuh M., Linderoth P., Dormann C. F., Arnold J. Adaptation of wild boar (Sus scrofa) activity in a human-dominated landscape. BMC Ecology. 2020; 20:4. https://doi.org/10.1186/s12898-019-0271-7Johann F., Handschuh M., Linderoth P., Dormann C. F., Arnold J. Adaptation of wild boar (Sus scrofa) activity in a human-dominated landscape. BMC Ecology. 2020; 20:4. https://doi.org/10.1186/s12898-019-0271-7Cukor J., Faltusová M., Vacek Z., Linda R., Skoták V., Václavek P., et al. Wild boar carcasses in the center of boar activity: crucial risks of ASF transmission. Frontiers in Veterinary Science. 2024; 11:1497361. https://doi.org/10.3389/fvets.2024.1497361Cukor J., Faltusová M., Vacek Z., Linda R., Skoták V., Václavek P., et al. Wild boar carcasses in the center of boar activity: crucial risks of ASF transmission. Frontiers in Veterinary Science. 2024; 11:1497361. https://doi.org/10.3389/fvets.2024.1497361Morelle K., Jezek M., Licoppe A., Podgorski T. Deathbed choice by ASF‐infected wild boar can help find carcasses. Transboundary and Emerging Diseases. 2019; 66 (5): 1821–1826. https://doi.org/10.1111/tbed.13267Morelle K., Jezek M., Licoppe A., Podgorski T. Deathbed choice by ASF‐infected wild boar can help find carcasses. Transboundary and Emerging Diseases. 2019; 66 (5): 1821–1826. https://doi.org/10.1111/tbed.13267Cukor J., Linda R., Václavek P., Šatrán P., Mahlerová K., Vacek Z., et al. Wild boar deathbed choice in relation to ASF: Are there any differences between positive and negative carcasses? Preventive Veterinary Medicine. 2020; 177:104943. https://doi.org/10.1016/j.prevetmed.2020.104943Cukor J., Linda R., Václavek P., Šatrán P., Mahlerová K., Vacek Z., et al. Wild boar deathbed choice in relation to ASF: Are there any differences between positive and negative carcasses? Preventive Veterinary Medicine. 2020; 177:104943. https://doi.org/10.1016/j.prevetmed.2020.104943Rogoll L., Schulz K., Staubach C., Oļševskis E., Seržants M., Lamberga K., et al. Identification of predilection sites for wild boar carcass search based on spatial analysis of Latvian ASF surveillance data. Scientific Reports. 2024; 14:382. https://doi.org/10.1038/s41598-023-50477-7Rogoll L., Schulz K., Staubach C., Oļševskis E., Seržants M., Lamberga K., et al. Identification of predilection sites for wild boar carcass search based on spatial analysis of Latvian ASF surveillance data. Scientific Reports. 2024; 14:382. https://doi.org/10.1038/s41598-023-50477-7Allepuz А., Hovari M., Masiulis M., Ciaravino G., Beltrán-Alcrudo D. Targeting the search of African swine fever-infected wild boar carcasses: A tool for early detection. Transboundary and Emerging Diseases. 2022; 69 (5): e1682–e1692. https://doi.org/10.1111/tbed.14504Allepuz А., Hovari M., Masiulis M., Ciaravino G., Beltrán-Alcrudo D. Targeting the search of African swine fever-infected wild boar carcasses: A tool for early detection. Transboundary and Emerging Diseases. 2022; 69 (5): e1682–e1692. https://doi.org/10.1111/tbed.14504Coelho I. M. P., Paiva M. T., da Costa A. J. A., Nicolino R. R. African swine fever: spread and seasonal patterns worldwide. Preventive Veterinary Medicine. 2025; 235:106401. https://doi.org/10.1016/j.prevetmed.2024.106401Coelho I. M. P., Paiva M. T., da Costa A. J. A., Nicolino R. R. African swine fever: spread and seasonal patterns worldwide. Preventive Veterinary Medicine. 2025; 235:106401. https://doi.org/10.1016/j.prevetmed.2024.106401Захарова О. И., Блохин А. А., Бурова О. А., Яшин И. В., Коренной Ф. И. Факторы риска распространения африканской чумы свиней среди диких кабанов в Российской Федерации. Ветеринария сегодня. 2024; 13 (1): 64–72. https://doi.org/10.29326/2304-196X-2024-13-1-64-72Zakharova O. I., Blokhin A. A., Burova O. A., Yashin I. V., Korennoy F. I. Risk factors for African swine fever spread in wild boar in the Russian Federation. Veterinary Science Today. 2024; 13 (1): 64–72. https://doi.org/10.29326/2304-196X-2024-13-1-64-72Probst C., Gethmann J., Amler S., Globig A., Knoll B., Conraths F. J. The potential role of scavengers in spreading African swine fever among wild boar. Scientific Reports. 2019; 9:11450. https://doi.org/10.1038/s41598019-47623-5Probst C., Gethmann J., Amler S., Globig A., Knoll B., Conraths F. J. The potential role of scavengers in spreading African swine fever among wild boar. Scientific Reports. 2019; 9:11450. https://doi.org/10.1038/s41598019-47623-5Nuanualsuwan S., Songkasupa T., Boonpornprasert P., Suwankitwat N., Lohlamoh W., Nuengjamnong C. Persistence of African swine fever virus on porous and non-porous fomites at environmental temperatures. Porcine Health Management. 2022; 8:34. https://doi.org/10.1186/s40813022-00277-8Nuanualsuwan S., Songkasupa T., Boonpornprasert P., Suwankitwat N., Lohlamoh W., Nuengjamnong C. Persistence of African swine fever virus on porous and non-porous fomites at environmental temperatures. Porcine Health Management. 2022; 8:34. https://doi.org/10.1186/s40813022-00277-8Tummeleht L., Häkkä S. S. S., Jürison M., Vilem A., Nurmoja I., Viltrop A. Wild boar (Sus scrofa) carcasses as an attraction for scavengers and a potential source for soil contamination with the African swine fever virus. Frontiers in Veterinary Science. 2024; 11:1305643. https://doi.org/10.3389/fvets.2024.1305643Tummeleht L., Häkkä S. S. S., Jürison M., Vilem A., Nurmoja I., Viltrop A. Wild boar (Sus scrofa) carcasses as an attraction for scavengers and a potential source for soil contamination with the African swine fever virus. Frontiers in Veterinary Science. 2024; 11:1305643. https://doi.org/10.3389/fvets.2024.1305643Probst C., Gethmann J., Amendt J., Lutz L., Teifke J. P., Conraths F. J. Estimating the postmortem interval of wild boar carcasses. Veterinary Sciences. 2020; 7 (1):6. https://doi.org/10.3390/vetsci7010006Probst C., Gethmann J., Amendt J., Lutz L., Teifke J. P., Conraths F. J. Estimating the postmortem interval of wild boar carcasses. Veterinary Sciences. 2020; 7 (1):6. https://doi.org/10.3390/vetsci7010006Pepin K. M., Golnar A. J., Abdo Z., Podgórski T. Ecological drivers of African swine fever virus persistence in wild boar populations: insight for control. Ecology and Evolution. 2020; 10 (6): 2846–2859. https://doi.org/10.1002/ece3.6100Pepin K. M., Golnar A. J., Abdo Z., Podgórski T. Ecological drivers of African swine fever virus persistence in wild boar populations: insight for control. Ecology and Evolution. 2020; 10 (6): 2846–2859. https://doi.org/10.1002/ece3.6100Davies K., Goatley L. C., Guinat C., Netherton C. L., Gubbins S., Dixon L. K., Reis A. L. Survival of African swine fever virus in excretions from pigs experimentally infected with the Georgia 2007/1 isolate. Transboundary and Emerging Diseases. 2017; 64 (2): 425–431. https://doi.org/10.1111/tbed.12381Davies K., Goatley L. C., Guinat C., Netherton C. L., Gubbins S., Dixon L. K., Reis A. L. Survival of African swine fever virus in excretions from pigs experimentally infected with the Georgia 2007/1 isolate. Transboundary and Emerging Diseases. 2017; 64 (2): 425–431. https://doi.org/10.1111/tbed.12381Prodelalova J., Kavanova L., Salat J., Moutelikova R., Kobzova S., Krasna M., et al. Experimental evidence of the long-term survival of infective African swine fever virus strain Ba71V in soil under different conditions. Pathogens. 2022; 11 (6):648. https://doi.org/10.3390/pathogens11060648Prodelalova J., Kavanova L., Salat J., Moutelikova R., Kobzova S., Krasna M., et al. Experimental evidence of the long-term survival of infective African swine fever virus strain Ba71V in soil under different conditions. Pathogens. 2022; 11 (6):648. https://doi.org/10.3390/pathogens11060648Carlson J., Fischer M., Zani L., Eschbaumer M., Fuchs W., Mettenleiter T., et al. Stability of African swine fever virus in soil and options to mitigate the potential transmission risk. Pathogens. 2020; 9 (11):977. https://doi.org/10.3390/pathogens9110977Carlson J., Fischer M., Zani L., Eschbaumer M., Fuchs W., Mettenleiter T., et al. Stability of African swine fever virus in soil and options to mitigate the potential transmission risk. Pathogens. 2020; 9 (11):977. https://doi.org/10.3390/pathogens9110977Mazur-Panasiuk N., Woźniakowski G. Natural inactivation of African swine fever virus in tissues: Influence of temperature and environmental conditions on virus survival. Veterinary Microbiology. 2020; 242:108609. https://doi.org/10.1016/j.vetmic.2020.108609Mazur-Panasiuk N., Woźniakowski G. Natural inactivation of African swine fever virus in tissues: Influence of temperature and environmental conditions on virus survival. Veterinary Microbiology. 2020; 242:108609. https://doi.org/10.1016/j.vetmic.2020.108609Блохин А. А., Бурова О. А., Торопова Н. Н., Захарова О. И., Яшин И. В., Коренной Ф. И. Мониторинг АЧС в дикой фауне: сохранность вируса в останках кабанов и методы дезинфекции (обзор литературы). Ветеринария. 2022; (3): 14–21. https://doi.org/10.30896/0042-4846.2022.25.3.14-21Blokhin A. A., Burova O. A., Toropova N. N., Zakharova O. I., Iashin I. V., Korennoy F. I. Monitoring ASF in wildlife: virus survival in wild boar carcasses and disinfection methods (review). Veterinariya. 2022; (3): 14–21. https:// doi.org/10.30896/0042-4846.2022.25.3.14-21 (in Russ.)Merta D., Mocała P., Pomykacz M., Frąckowiak W. Autumn-winter diet and fat reserves of wild boars (Sus scrofa) inhabiting forest and forest-farmland environment in south-western Poland. Folia Zoologica. 2014; 63 (2): 95–102. https://doi.org/10.25225/fozo.v63.i2.a7.2014Merta D., Mocała P., Pomykacz M., Frąckowiak W. Autumn-winter diet and fat reserves of wild boars (Sus scrofa) inhabiting forest and forest-farmland environment in south-western Poland. Folia Zoologica. 2014; 63 (2): 95–102. https://doi.org/10.25225/fozo.v63.i2.a7.2014Cukor J., Linda R., Václavek P., Mahlerová K., Šatrán P., Havránek F. Confirmed cannibalism in wild boar and its possible role in African swine fever transmission. Transboundary and Emerging Diseases. 2020; 67 (3): 1068–1073. https://doi.org/10.1111/tbed.13468Cukor J., Linda R., Václavek P., Mahlerová K., Šatrán P., Havránek F. Confirmed cannibalism in wild boar and its possible role in African swine fever transmission. Transboundary and Emerging Diseases. 2020; 67 (3): 1068–1073. https://doi.org/10.1111/tbed.13468Sánchez-Cordón P. J., Lean F. Z. X., Batten C., Steinbach F., Neimanis A., Le Potier M. F., et al. Comparative evaluation of disease dynamics in wild boar and domestic pigs experimentally inoculated intranasally with the European highly virulent African swine fever virus genotype II strain “Armenia 2007”. Vet­erinary Research. 2024; 55:89. https://doi.org/10.1186/s13567-024-01343-5Sánchez-Cordón P. J., Lean F. Z. X., Batten C., Steinbach F., Neimanis A., Le Potier M. F., et al. Comparative evaluation of disease dynamics in wild boar and domestic pigs experimentally inoculated intranasally with the European highly virulent African swine fever virus genotype II strain “Armenia 2007”. Vet­erinary Research. 2024; 55:89. https://doi.org/10.1186/s13567-024-01343-5Rietz J., Ischebeck S., Conraths F. J., Probst C., Zedrosser A., Fiderer C., et al. Scavenger-induced scattering of wild boar carcasses over large distances and its implications for disease management. Journal of Environmental Management. 2024; 365:121554. https://doi.org/10.1016/j.jenvman.2024.121554Rietz J., Ischebeck S., Conraths F. J., Probst C., Zedrosser A., Fiderer C., et al. Scavenger-induced scattering of wild boar carcasses over large distances and its implications for disease management. Journal of Environmental Management. 2024; 365:121554. https://doi.org/10.1016/j.jenvman.2024.121554Hyun C.-U., Park M., Lee W. Y. Remotely piloted aircraft system (RPAS)-based wildlife detection: a review and case studies in maritime Antarctica. Animals. 2020; 10 (12):2387. https://doi.org/10.3390/ani10122387Hyun C.-U., Park M., Lee W. Y. Remotely piloted aircraft system (RPAS)-based wildlife detection: a review and case studies in maritime Antarctica. Animals. 2020; 10 (12):2387. https://doi.org/10.3390/ani10122387Просеков А. Ю. Характеристика и ключевые ограничения традиционных методов учета охотничьих животных и цифровые технологии для решения существующих проблем (обзор). Аграрная наука ЕвроСеверо­Востока. 2020; 21 (4): 341–354. https://doi.org/10.30766/20729081.2020.21.4.341-354Prosekov A. Yu. Characteristics and key limitations of traditional methods for accounting hunting animals and digital technologies for solving the existing problems (review). Agricultural Science Euro­North­East. 2020; 21 (4): 341–354. https://doi.org/10.30766/2072-9081.2020.21.4.341-354 (in Russ.)Prosekov A., Kuznetsov A., Rada A., Ivanova S. Methods for monitoring large terrestrial animals in the wild. Forests. 2020; 11 (8):808. https://doi.org/10.3390/f11080808Prosekov A., Kuznetsov A., Rada A., Ivanova S. Methods for monitoring large terrestrial animals in the wild. Forests. 2020; 11 (8):808. https://doi.org/10.3390/f11080808Tubis A. A., Poturaj H., Dereń K., Żurek A. Risks of drone use in light of literature studies. Sensors. 2024; 24 (4):1205. https://doi.org/10.3390/s24041205Tubis A. A., Poturaj H., Dereń K., Żurek A. Risks of drone use in light of literature studies. Sensors. 2024; 24 (4):1205. https://doi.org/10.3390/s24041205Ivanova S., Prosekov A. Hunting resource management by population size control by remote sensing using an unmanned aerial vehicle. Nature Environment and Pollution Technology. 2024; 23 (1): 391–399. https://doi.org/10.46488/NEPT.2024.v23i01.033Ivanova S., Prosekov A. Hunting resource management by population size control by remote sensing using an unmanned aerial vehicle. Nature Environment and Pollution Technology. 2024; 23 (1): 391–399. https://doi.org/10.46488/NEPT.2024.v23i01.033Lee M. J., Voss S. C., Franklin D., Dadour I. R. Preliminary investigation of aircraft mounted thermal imaging to locate decomposing remains via the heat produced by larval aggregations. Forensic Science International. 2018; 289: 175–185. https://doi.org/10.1016/j.forsciint.2018.05.028Lee M. J., Voss S. C., Franklin D., Dadour I. R. Preliminary investigation of aircraft mounted thermal imaging to locate decomposing remains via the heat produced by larval aggregations. Forensic Science International. 2018; 289: 175–185. https://doi.org/10.1016/j.forsciint.2018.05.028Butters O., Krosch M. N., Roberts M., MacGregor D. Application of forward-looking infrared (FLIR) imaging from an unmanned aerial platform in the search for decomposing remains. Journal of Forensic Sciences. 2021; 66 (1): 347–355. https://doi.org/10.1111/1556-4029.14581Butters O., Krosch M. N., Roberts M., MacGregor D. Application of forward-looking infrared (FLIR) imaging from an unmanned aerial platform in the search for decomposing remains. Journal of Forensic Sciences. 2021; 66 (1): 347–355. https://doi.org/10.1111/1556-4029.14581Peksa J., Mamchur D. A review on the state of the art in copter drones and flight control systems. Sensors. 2024; 24 (11):3349. https://doi.org/10.3390/s24113349Peksa J., Mamchur D. A review on the state of the art in copter drones and flight control systems. Sensors. 2024; 24 (11):3349. https://doi.org/10.3390/s24113349Askari M., Benciolini M., Phan H. V., Stewart W., Ijspeert A. J., Floreano D. Crash-perching on vertical poles with a hugging-wing robot. Communications Engineering. 2024; 3:98. https://doi.org/10.1038/s44172024-00241-0Askari M., Benciolini M., Phan H. V., Stewart W., Ijspeert A. J., Floreano D. Crash-perching on vertical poles with a hugging-wing robot. Communications Engineering. 2024; 3:98. https://doi.org/10.1038/s44172024-00241-0Mechan F., Bartonicek Z., Malone D., Lees R. S. Unmanned aerial vehicles for surveillance and control of vectors of malaria and other vector- borne diseases. Malaria Journal. 2023; 22:23. https://doi.org/10.1186/s12936-022-04414-0Mechan F., Bartonicek Z., Malone D., Lees R. S. Unmanned aerial vehicles for surveillance and control of vectors of malaria and other vector- borne diseases. Malaria Journal. 2023; 22:23. https://doi.org/10.1186/s12936-022-04414-0Longmore S. N., Collins R. P., Pfeifer S., Fox S. E., Mulero-Pázmány M., Bezombes F., et al. Adapting astronomical source detection software to help detect animals in thermal images obtained by unmanned aerial systems. International Journal of Remote Sensing. 2017; 38 (8–10): 2623–2638. https://doi.org/10.1080/01431161.2017.1280639Longmore S. N., Collins R. P., Pfeifer S., Fox S. E., Mulero-Pázmány M., Bezombes F., et al. Adapting astronomical source detection software to help detect animals in thermal images obtained by unmanned aerial systems. International Journal of Remote Sensing. 2017; 38 (8–10): 2623–2638. https://doi.org/10.1080/01431161.2017.1280639Prosekov A., Vesnina A., Atuchin V., Kuznetsov A. Robust algorithms for drone-assisted monitoring of big animals in harsh conditions of Siberian winter forests: recovery of European elk (Alces alces) in Salair mountains. Animals. 2022; 12 (12):1483. https://doi.org/10.3390/ani12121483Prosekov A., Vesnina A., Atuchin V., Kuznetsov A. Robust algorithms for drone-assisted monitoring of big animals in harsh conditions of Siberian winter forests: recovery of European elk (Alces alces) in Salair mountains. Animals. 2022; 12 (12):1483. https://doi.org/10.3390/ani12121483Zhou M., Elmore J. A., Samiappan S., Evans K. O., Pfeiffer M. B., Blackwell B. F., Iglay R. B. Improving animal monitoring using small unmanned aircraft systems (sUAS) and deep learning networks. Sensors. 2021; 21 (17):5697. https://doi.org/10.3390/s21175697Zhou M., Elmore J. A., Samiappan S., Evans K. O., Pfeiffer M. B., Blackwell B. F., Iglay R. B. Improving animal monitoring using small unmanned aircraft systems (sUAS) and deep learning networks. Sensors. 2021; 21 (17):5697. https://doi.org/10.3390/s21175697Samiappan S., Krishnan B. S., Dehart D., Jones L. R., Elmore J. A., Evans K. O., Iglay R. B. Aerial wildlife image repository for animal monitoring with drones in the age of artificial intelligence. Database. 2024; 2024:baae070. https://doi.org/10.1093/database/baae070Samiappan S., Krishnan B. S., Dehart D., Jones L. R., Elmore J. A., Evans K. O., Iglay R. B. Aerial wildlife image repository for animal monitoring with drones in the age of artificial intelligence. Database. 2024; 2024:baae070. https://doi.org/10.1093/database/baae070

The authors declare that there are no conflicts of interest present.