Abstract
Pastoral activities bring several benefits to the ecosystem and rural communities. These activities are already carried out daily with goats, cows and sheep in Portugal. Still, they could be better applied to take advantage of their benefits. Most of these pastoral ecosystem services are not remunerated, indicating a lack of making these activities more attractive to bring returns to shepherds, breeders and landowners. The monitoring of these activities provides data to value these services, besides being able to indicate directly to the shepherds’ routes to drive their flocks and the respective return. There are devices in the market that perform this monitoring, but they are not adaptable to the circumstances and challenges required in the Northeast of Portugal. This work addresses a system to perform animals tracking, and the development of a test platform, through long-range technologies for transmission using LoRaWAN architecture. The results demonstrated the use of LoRaWAN in tracking services, allowing to conclude about the viability of the proposed methodology and the direction for future works.
Supported by FEDER (Fundo Europeu de Desenvolvimento Regional).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Roe, E., Huntsinger, L., Labnow, K.: High reliability pastoralism. J. Arid Environ. 39(1), 39–55 (1998)
Castro, M., Castro, J., Gómez Sal, A.: L’utilisation du territoire par les petits ruminants dans la région de montagne de trás-os-montes, au portugal. Options Méditerranéennes. Série A, A Séminaires Méditerranéens, no 61, 249–254 (2004)
Bernues, A., Rodríguez-Ortega, T., Ripoll-Bosch, R., Alfnes, F.: Socio-cultural and economic valuation of ecosystem services provided by mediterranean mountain agroecosystems. PloS One 9(7), e102479 (2014)
Castro, M., Ameray, A., Castro, J.P.: A new approach to quantify grazing pressure under mediterranean pastoral systems using GIS and remote sensing. Int. J. Remote Sens. 41(14), 5371–5387 (2020)
Nóbrega, L., Tavares, A., Cardoso, A., Gonçalves, P.: Animal monitoring based on IoT technologies. In: 2018 IoT Vertical and Topical Summit on Agriculture-Tuscany (IOT Tuscany), pp. 1–5. IEEE (2018)
Guide to animal tracking. https://outdooraction.princeton.edu/nature/guide-animal-tracking. Accessed 15 May 2021
Bozek, K., Hebert, L., Portugal, Y., Stephens, G.J.: Markerless tracking of an entire honey bee colony. Nat. Commun. 12(1), 1–13 (2021)
Ryan, P., Petersen, S., Peters, G., Grémillet, D.: GPS tracking a marine predator: the effects of precision, resolution and sampling rate on foraging tracks of African penguins. Mar. Biol. 145(2), 215–223 (2004)
Panicker, J.G., Azman, M., Kashyap, R.: A LoRa wireless mesh network for wide-area animal tracking. In: 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), pp. 1–5. IEEE (2019)
Maroto-Molina, F., et al.: A low-cost IoT-based system to monitor the location of a whole herd. Sensors 19(10), 2298 (2019)
Milsar. https://milsar.com/. Accessed 15 May 2021
Digital animal. https://digitanimal.pt/. Accessed 15 May 2021
Movebank. https://www.movebank.org/cms/movebank-main. Accessed 15 May 2021
Brito, T., Pereira, A.I., Lima, J., Castro, J.P., Valente, A.: Optimal sensors positioning to detect forest fire ignitions. In: Proceedings of the 9th International Conference on Operations Research and Enterprise Systems, pp. 411–418 (2020)
Brito, T., Pereira, A.I., Lima, J., Valente, A.: Wireless sensor network for ignitions detection: an IoT approach. Electronics 9(6), 893 (2020)
Azevedo, B.F., Brito, T., Lima, J., Pereira, A.I.: Optimum sensors allocation for a forest fires monitoring system. Forests 12(4), 453 (2021)
Brito, T., Azevedo, B.F., Valente, A., Pereira, A.I., Lima, J., Costa, P.: Environment monitoring modules with fire detection capability based on IoT methodology. In: Paiva, S., Lopes, S.I., Zitouni, R., Gupta, N., Lopes, S.F., Yonezawa, T. (eds.) SmartCity360\(^{\circ } \) 2020. LNICST, vol. 372, pp. 211–227. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-76063-2_16
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Zorawski, M., Brito, T., Castro, J., Castro, J.P., Castro, M., Lima, J. (2021). An IoT Approach for Animals Tracking. In: Pereira, A.I., et al. Optimization, Learning Algorithms and Applications. OL2A 2021. Communications in Computer and Information Science, vol 1488. Springer, Cham. https://doi.org/10.1007/978-3-030-91885-9_19
Download citation
DOI: https://doi.org/10.1007/978-3-030-91885-9_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-91884-2
Online ISBN: 978-3-030-91885-9
eBook Packages: Computer ScienceComputer Science (R0)