INVESTIGATING THE IMPACT OF ECONOMIC, POLITICAL, AND SOCIAL FACTORS ON AUGMENTED REALITY TECHNOLOGY ACCEPTANCE IN AGRICULTURE (LIVESTOCK FARMING) SECTOR IN DEVELOPING COUNTRIES
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The discussion of the factors affecting the tendency to accept new technologies in developing countries is very important. Lack of use of modern technologies in developing countries, especially in the agricultural (livestock farming) sector, leads to negative effects on the quality and quantity of products and the country loses its ability to compete in the international arena. The main purpose of this study is to investigate the factors affecting on Augmented Reality technology acceptance in the agricultural (livestock) sector of Iran. In this research, the dependent variable is a qualitative variable that is classified into five levels based on the theory of experts using the SWARA method. The dependent variable indicates the ability (awareness) and capability (financially) of a person to accept AR technology. We used the Multinomial Logit model due to the dependent variable is nominal and has more than two categories. The results showed that, the variables of public participation, and education have a significant effect on the willingness to adopt Augmented Reality technology at all levels among farmers. But variable costs and the number of family labor do not have a significant effect on the willingness to accept Augmented Reality technology. The policy recommendations of this research are that councils can play an important role in raising the level of public participation and conveying the demands of the people to the government. To do this, they must receive the necessary training in order to attract public participation. This is possible through training workshops to increase the level of farmers’ awareness.
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Alam,M.F. Katsikas, S. Beltramello, O. and Hadjiefthymiades, S. (2017). Augmented and virtual reality based monitoring and safety system: A prototype IoT platform. J. Netw. Comput. Appl. 89: 109–119. https://doi.org/10.1016/j.jnca.2017.03.022
Applebaugh, J, Governance Working Group. power-point presentation, National Defense University and ISAF, slide 2. 2010. https://www.slideteam.net/governance-model-powerpoint.
Bauer, A. Neog, D.R. Dicko, A.H. Pai, D.K. Faure, F. Palombi, and O. Troccaz, J. (2017). Anatomical augmented reality with 3D commodity tracking and image-space alignment. Comput. Graph. 69:140–153. DOI:10.1016/j.cag.2017.10.008
Bitzar, V. Bertus, W. and Steenhuijsen, P. de. (2016). The governance of agricultural extension systems, kit working papers. https://www.kit.nl/wp-content/uploads.
Cˇ olakovic´, A. Hadžialic´,M. (2018). Internet of Things (IoT): A review of enabling technologies, challenges, and open research issues. Comput. Netw. 144:17–39. DOI:10.1016/j.comnet.2018.07.017
Cari,a M. Todde, G. and Pazzona, A. (2019). Evaluation of automated in-line precision dairy farming technology implementation in three dairy farms in Italy. Front Agric. Sci. Eng. 6: 181–187. doi: 10.15302/J-FASE-2019252.
Caria, M., Boselli, C., Murgia, L., Rosati, R., Pazzona, A. (2013). Influence of low vacuum levels on milking characteristics of sheep, goat and buffalo. J. Agric. Eng. 44: 217–220. doi: 10.4081/jae.2013.285.
Chatzopoulos, D. Bermejo, C. Huang, Z. Hui, P. (2017). Mobile augmented reality survey: From where we are to where we go. IEEE Access, 5: 6917–6950. DOI: 10.1109/ACCESS.2017.2698164
Daponte, P. Vito, L.D. Picariello, F. and Riccio, M. (2014). State of the art and future developments of the Augmented Reality for measurement applications. Measurement, 57: 53–70. https://doi.org/10.1016/j.measurement.2014.07.009
Dekker, R., and Bekkers, V. (2015). The contingency of governments' responsiveness to the virtual public sphere: A systematic literature review and meta-synthesis, Government Information Quarterly, 32: 496–505. https://doi.org/10.1016/j.giq.2015.09.007
Durrant-Whyte, H. Bailey, T. (2006). Simultaneous Localization and Mapping: Part I. IEEE Robot. Autom. Mag. 13: 99–110. DOI: 10.1109/MRA.2006.1638022
ElSayed, N.A.M. Thomas, B.H. Marriott, K. Piantadosi, J. Smith, R.T. (2016). Situated Analytics: Demonstrating immersive analytical tools with Augmented Reality. J. Vis. Lang. Comput. 36: 13–23.
Fournel, S., Rousseau, A., Laberge, B. (2017). Rethinking environment control strategy of confined animal housing systems through precision livestock farming. Biosyst. Eng. 155: 96–123. doi: 10.1016/j.biosystemseng.2016.12.005.
Gomes, P., Olaverri-Monreal, C., Ferreira, M. (2012). Making Vehicles Transparent Through V2V Video Streaming. IEEE Trans. Intell. Transp. Syst. 13: 930–938. DOI:10.1109/TITS.2012.2188289
Gorecky, D. Schmitt, M. Loskyll, M. Zühlke, D. (2014). Human-machine-interaction in the Industry 4.0 era. In Proceedings of the 12th IEEE International Conference on Industrial Informatics (INDIN), Porto Alegre, Brazil, 27–30 July, 289–294. DOI:10.1109/INDIN.2014.6945523
Gushima, K, and Nakajima, T. (2017). A Design Space for Virtuality-Introduced Internet of Things. Future Internet;
9, 60. DOI:10.3390/fi9040060
Halachmi I., Guarino M., Bewley J., Pastell M. (2019). Smart Animal Agriculture: Application of Real-Time Sensors to Improve Animal Well-Being and Production. Annu. Rev. Anim. Biosci. 7: 403–425. doi: 10.1146/annurev-animal-020518-114851.
Hamuda, E., Ginley, B.M., Glavin, M., Jones, E. (2018). Improved image processing-based crop detection using Kalman filtering and the Hungarian algorithm. Comput. Electron. Agric. 148: 37–44. DOI:10.1016/j.compag.2018.02.027
Hamuda, E., Ginley, B.M., Glavin, M., Jones, E. (2017). Automatic crop detection under field conditions using the HSV colour space and space and morphological operations. Comput. Electron. Agric. 133: 97–107. DOI:10.1016/j.compag.2016.11.021
Hirschmüller, H. (2017). Improvements in Real-Time Correlation-Based Stereo Vision. In Proceedings of the IEEE Workshop on Stereo and Multi-Baseline Vision, Kauai, HI, USA, 9–10 December 2001. http://dx.doi.org/10.1109/SMBV.2001.988772
Hirschmüller, H., Innocent, P.R., and Garibaldi, J. (2002). Real-time Correlation-Based Stereo Vision with Reduced Border Errors. Int. J. Comput. Vis. 47: 229–246. https://link.springer.com/article/10.1023/A:1014554110407
Hockstein, N.G., Gourin, C., Faust, R., and Terris, D.J. (2007). A history of robots: From science fiction to surgical robotics. J. Rob. Surg. 1: 113–118. doi: 10.1007/s11701-007-0021-2
Huang, J.M., Ong, S.K.., and Nee, A.Y.C. (2015). Real-time finite element structural analysis in augmented reality. Advances in Engineering Software. Adv. Eng. Softw. 87: 43–56. https://doi.org/10.1016/j.advengsoft.2015.04.014
Janssen, M., and Van der Voort, H. (2016). Adaptive governance: Towards a stable, accountable and responsive government’, Government Information Quarterly, 33: 1-5. https://doi.org/10.1016/j.giq.2016.02.003
Janssen, c. (2018). Consumer Acceptance of Mobile Augmented Reality Shopping Applications in Stationary Retail Trade. Bachelor thesis. URN: urn:nbn:se:miun:diva-34171. OAI: oai:DiVA.org:miun-34171. Diva, id: diva2: 1232271
Jeone, B., and Yoon, J. (2017). Competitive Intelligence Analysis of Augmented Reality Technology Using Patent Information. Sustainability. 9, 497. https://doi.org/10.3390/su9040497
King T.M., LeBlanc S.J., Pajor E.A., Wright T.C., DeVries T.J. (2018). Behaviour and productivity of cows milked in automated systems before diagnosis of health disorders in early lactation. J. Dairy Sci. 101: 4343–4356. doi: 10.3168/jds.2017-13686
Ku, K.., Chia, K.W., and Cheok, A.D. (2008). Real-time camera tracking for marker-less and unprepared augmented reality environments. Image Vis. Comput. 26: 673–689. DOI:10.1016/j.imavis.2007.08.015
Kehoe, B., Patil, S., Abbeel, P., and Goldberg, K. (2015). A survey of research on cloud robotics and automation. IEEE Trans. Autom. Sci. Eng. 12: 398–409. DOI: 10.1109/TASE.2014.2376492
Lee, A.; Jang, I. (2018). Robust Multithreaded Object Tracker through Occlusions for Spatial Augmented Reality.
Etri J. 40: 246–256. https://doi.org/10.4218/etrij.2017-0047
Liao, M.S. Chen, S.F. Chou, C.Y. Chen, H.Y.; Yeh, S.H. Chang, Y.C. and Jiang, J.A. (2017). On precisely relating the growth of Phalaenopsis leaves to greenhouse environmental factors by using an IoT-based monitoring system. Comput. Electron. Agric. 136: 125–139. https://doi.org/10.1016/j.compag.2017.03.003
Lima, J.P. Roberto, R. Simões, F. Almeida, M. Figueiredo, L. Teixeira, J.M. and Teichrieb, V. (2017). Markerless tracking system for augmented reality in the automotive industry. Expert Syst. Appl. 82: 100–114. https://doi.org/10.1016/j.eswa.2017.03.060
Liao, M.S. Chen, S.F. Chou, C.Y. Chen, H.Y. Yeh, S.H. Chang, Y.C. Jiang, J.A. (2017). On precisely relating the growth of Phalaenopsis leaves to greenhouse environmental factors by using an IoT-based monitoring system. Comput. Electron. Agric. 136: 125–139. https://doi.org/10.1016/j.compag.2017.03.003
MacKenzie, I.S. (1995). Input devices and interaction techniques for advanced computing. In Virtual Environments and Advanced Interface Design; Oxford University Press: Oxford, UK, June 1995; 437–470.
Makhataeva, Z.; Zhakatayev, A.; Varol, H.A. (2019). Safety Aura Visualization for Variable Impedance Actuated Robots. In Proceedings of the IEEE/SICE International Symposium on System Integration (SII), Paris, France,
14–16 January 2019; 805–810. https://doi 10.1109/SII.2019.8700332
Manian, A. And Ronaghi, m. (2016). Providing a comprehensive framework for implementing Internet marketing using the meta-combined method. University of Tehran Press. 7 : 901-920. https://doi.10.22059/JIBM.2015.57097
Muraleedharan. K., (2008). Dynamics of People Participation in Development: A Study with Special Reference to Women Participation in the Local Level Planning in Kerala, Eldis Participation Resource Guide, Handbook of Cultural Geography, Sage, London.
Phupattanasilp, P., and Tong, S.R. (2016). Application of multiple view geometry for object positioning and inquiry in agricultural augmented reality. In Proceedings of the 2nd International Conference on Agricultural and
Biological Sciences, Shanghai, China, 23–26.
Primmer, E. and Kyllonen., S. (2008). Goals for Public Participation Implied by Sustainable Development and the Preparatory Process of the Finnish National Forest Program, Forest Policy and Economics, 8( 8): 838– 853. https://doi.org/10.1016/j.forpol.2005.01.002
Rashid, Z., Melià-Seguí, J., Pous, R., and Peig, E. (2017). Using Augmented Reality and Internet of Things to improve accessibility of people with motor disabilities in the context of Smart Cities. Future Gener. Comput. Syst. 76: 248–261. https://doi.org/10.1016/j.future.2016.11.030
Soma, K., Onwezen,M., Salverda, I.E., and I van Dam, R. (2016). Roles of citizens in environmental governance in the Information Age four theoretical perspectives. Current Opinion in Environmental Sustainability, 18: 122–130. https://doi.org/10.1016/j.cosust.2015.12.009
Sutherland, I.E. The Ultimate Display. In Proceedings of the IFIP Congress; Macmillan and Co.: London, UK,
1965; pp. 506–508. http://www.wired.com/beyond_the_beyond/2009/09/augmented-reality-the-ultimate-display-by-ivan-sutherland-1965/
Tati´c, D., and Teši´c, B. (2017). The application of augmented reality technologies for the improvement of occupational safety in an industrial environment. Comput. Ind. 85, 1–10. https://doi.org/10.1016/j.compind.2016.11.004
Teitel, M.A. (1990). The Eyephone: A head-mounted stereo display. In Stereoscopic Displays and Applications; SPIE: Bellingham, DC, USA, 1256: 168–171. https://doi.org/10.1117/12.19902
Todde G., Caria M., Gambella F., Pazzona A. (2017). Energy and Carbon Impact of Precision Livestock Farming Technologies Implementation in the Milk Chain: From Dairy Farm to Cheese Factory. Agriculture. 7:79. doi: 10.3390/agriculture7100079.
Tullo E., Finzi A., Guarino M. (2019). Environmental impact of livestock farming and Precision Livestock Farming as a mitigation strategy. Sci. Total Environ. 650: 2751–2760. doi: 10.1016/j.scitotenv.2018.10.018.
Todde G., Murgia L., Caria M., Pazzona A. (2016). A multivariate statistical analysis approach to characterize mechanization, structural and energy profile in Italian dairy farms. Energy Rep. 2: 129–134. doi: 10.1016/j.egyr.2016.05.006.
Wathes C.M., Kristensenb H.H., Aertsc J.M., Berckmans D. (2008). Is precision livestock farming an engineer’s daydream or nightmare, an animal’s friend or foe, and a farmer’s panacea or pitfall? Comput. Electron. Agric. 64: 2–10. doi: 10.1016/j.compag.2008.05.005.
Velázquez, F. and Morales Méndez, G. (2018). Augmented Reality and Mobile Devices: A Binominal Methodological Resource for Inclusive Education (SDG 4). An Example in Secondary Education. Sustainability 10: 34-46. DOI:10.3390/su10103446
Alam,M.F. Katsikas, S. Beltramello, O. and Hadjiefthymiades, S. (2017). Augmented and virtual reality based monitoring and safety system: A prototype IoT platform. J. Netw. Comput. Appl. 89: 109–119. https://doi.org/10.1016/j.jnca.2017.03.022
Applebaugh, J, Governance Working Group. power-point presentation, National Defense University and ISAF, slide 2. 2010. https://www.slideteam.net/governance-model-powerpoint.
Bauer, A. Neog, D.R. Dicko, A.H. Pai, D.K. Faure, F. Palombi, and O. Troccaz, J. (2017). Anatomical augmented reality with 3D commodity tracking and image-space alignment. Comput. Graph. 69:140–153. DOI:10.1016/j.cag.2017.10.008
Bitzar, V. Bertus, W. and Steenhuijsen, P. de. (2016). The governance of agricultural extension systems, kit working papers. https://www.kit.nl/wp-content/uploads.
Cˇ olakovic´, A. Hadžialic´,M. (2018). Internet of Things (IoT): A review of enabling technologies, challenges, and open research issues. Comput. Netw. 144:17–39. DOI:10.1016/j.comnet.2018.07.017
Cari,a M. Todde, G. and Pazzona, A. (2019). Evaluation of automated in-line precision dairy farming technology implementation in three dairy farms in Italy. Front Agric. Sci. Eng. 6: 181–187. doi: 10.15302/J-FASE-2019252.
Caria, M., Boselli, C., Murgia, L., Rosati, R., Pazzona, A. (2013). Influence of low vacuum levels on milking characteristics of sheep, goat and buffalo. J. Agric. Eng. 44: 217–220. doi: 10.4081/jae.2013.285.
Chatzopoulos, D. Bermejo, C. Huang, Z. Hui, P. (2017). Mobile augmented reality survey: From where we are to where we go. IEEE Access, 5: 6917–6950. DOI: 10.1109/ACCESS.2017.2698164
Daponte, P. Vito, L.D. Picariello, F. and Riccio, M. (2014). State of the art and future developments of the Augmented Reality for measurement applications. Measurement, 57: 53–70. https://doi.org/10.1016/j.measurement.2014.07.009
Dekker, R., and Bekkers, V. (2015). The contingency of governments' responsiveness to the virtual public sphere: A systematic literature review and meta-synthesis, Government Information Quarterly, 32: 496–505. https://doi.org/10.1016/j.giq.2015.09.007
Durrant-Whyte, H. Bailey, T. (2006). Simultaneous Localization and Mapping: Part I. IEEE Robot. Autom. Mag. 13: 99–110. DOI: 10.1109/MRA.2006.1638022
ElSayed, N.A.M. Thomas, B.H. Marriott, K. Piantadosi, J. Smith, R.T. (2016). Situated Analytics: Demonstrating immersive analytical tools with Augmented Reality. J. Vis. Lang. Comput. 36: 13–23.
Fournel, S., Rousseau, A., Laberge, B. (2017). Rethinking environment control strategy of confined animal housing systems through precision livestock farming. Biosyst. Eng. 155: 96–123. doi: 10.1016/j.biosystemseng.2016.12.005.
Gomes, P., Olaverri-Monreal, C., Ferreira, M. (2012). Making Vehicles Transparent Through V2V Video Streaming. IEEE Trans. Intell. Transp. Syst. 13: 930–938. DOI:10.1109/TITS.2012.2188289
Gorecky, D. Schmitt, M. Loskyll, M. Zühlke, D. (2014). Human-machine-interaction in the Industry 4.0 era. In Proceedings of the 12th IEEE International Conference on Industrial Informatics (INDIN), Porto Alegre, Brazil, 27–30 July, 289–294. DOI:10.1109/INDIN.2014.6945523
Gushima, K, and Nakajima, T. (2017). A Design Space for Virtuality-Introduced Internet of Things. Future Internet;
9, 60. DOI:10.3390/fi9040060
Halachmi I., Guarino M., Bewley J., Pastell M. (2019). Smart Animal Agriculture: Application of Real-Time Sensors to Improve Animal Well-Being and Production. Annu. Rev. Anim. Biosci. 7: 403–425. doi: 10.1146/annurev-animal-020518-114851.
Hamuda, E., Ginley, B.M., Glavin, M., Jones, E. (2018). Improved image processing-based crop detection using Kalman filtering and the Hungarian algorithm. Comput. Electron. Agric. 148: 37–44. DOI:10.1016/j.compag.2018.02.027
Hamuda, E., Ginley, B.M., Glavin, M., Jones, E. (2017). Automatic crop detection under field conditions using the HSV colour space and space and morphological operations. Comput. Electron. Agric. 133: 97–107. DOI:10.1016/j.compag.2016.11.021
Hirschmüller, H. (2017). Improvements in Real-Time Correlation-Based Stereo Vision. In Proceedings of the IEEE Workshop on Stereo and Multi-Baseline Vision, Kauai, HI, USA, 9–10 December 2001. http://dx.doi.org/10.1109/SMBV.2001.988772
Hirschmüller, H., Innocent, P.R., and Garibaldi, J. (2002). Real-time Correlation-Based Stereo Vision with Reduced Border Errors. Int. J. Comput. Vis. 47: 229–246. https://link.springer.com/article/10.1023/A:1014554110407
Hockstein, N.G., Gourin, C., Faust, R., and Terris, D.J. (2007). A history of robots: From science fiction to surgical robotics. J. Rob. Surg. 1: 113–118. doi: 10.1007/s11701-007-0021-2
Huang, J.M., Ong, S.K.., and Nee, A.Y.C. (2015). Real-time finite element structural analysis in augmented reality. Advances in Engineering Software. Adv. Eng. Softw. 87: 43–56. https://doi.org/10.1016/j.advengsoft.2015.04.014
Janssen, M., and Van der Voort, H. (2016). Adaptive governance: Towards a stable, accountable and responsive government’, Government Information Quarterly, 33: 1-5. https://doi.org/10.1016/j.giq.2016.02.003
Janssen, c. (2018). Consumer Acceptance of Mobile Augmented Reality Shopping Applications in Stationary Retail Trade. Bachelor thesis. URN: urn:nbn:se:miun:diva-34171. OAI: oai:DiVA.org:miun-34171. Diva, id: diva2: 1232271
Jeone, B., and Yoon, J. (2017). Competitive Intelligence Analysis of Augmented Reality Technology Using Patent Information. Sustainability. 9, 497. https://doi.org/10.3390/su9040497
King T.M., LeBlanc S.J., Pajor E.A., Wright T.C., DeVries T.J. (2018). Behaviour and productivity of cows milked in automated systems before diagnosis of health disorders in early lactation. J. Dairy Sci. 101: 4343–4356. doi: 10.3168/jds.2017-13686
Ku, K.., Chia, K.W., and Cheok, A.D. (2008). Real-time camera tracking for marker-less and unprepared augmented reality environments. Image Vis. Comput. 26: 673–689. DOI:10.1016/j.imavis.2007.08.015
Kehoe, B., Patil, S., Abbeel, P., and Goldberg, K. (2015). A survey of research on cloud robotics and automation. IEEE Trans. Autom. Sci. Eng. 12: 398–409. DOI: 10.1109/TASE.2014.2376492
Lee, A.; Jang, I. (2018). Robust Multithreaded Object Tracker through Occlusions for Spatial Augmented Reality.
Etri J. 40: 246–256. https://doi.org/10.4218/etrij.2017-0047
Liao, M.S. Chen, S.F. Chou, C.Y. Chen, H.Y.; Yeh, S.H. Chang, Y.C. and Jiang, J.A. (2017). On precisely relating the growth of Phalaenopsis leaves to greenhouse environmental factors by using an IoT-based monitoring system. Comput. Electron. Agric. 136: 125–139. https://doi.org/10.1016/j.compag.2017.03.003
Lima, J.P. Roberto, R. Simões, F. Almeida, M. Figueiredo, L. Teixeira, J.M. and Teichrieb, V. (2017). Markerless tracking system for augmented reality in the automotive industry. Expert Syst. Appl. 82: 100–114. https://doi.org/10.1016/j.eswa.2017.03.060
Liao, M.S. Chen, S.F. Chou, C.Y. Chen, H.Y. Yeh, S.H. Chang, Y.C. Jiang, J.A. (2017). On precisely relating the growth of Phalaenopsis leaves to greenhouse environmental factors by using an IoT-based monitoring system. Comput. Electron. Agric. 136: 125–139. https://doi.org/10.1016/j.compag.2017.03.003
MacKenzie, I.S. (1995). Input devices and interaction techniques for advanced computing. In Virtual Environments and Advanced Interface Design; Oxford University Press: Oxford, UK, June 1995; 437–470.
Makhataeva, Z.; Zhakatayev, A.; Varol, H.A. (2019). Safety Aura Visualization for Variable Impedance Actuated Robots. In Proceedings of the IEEE/SICE International Symposium on System Integration (SII), Paris, France,
14–16 January 2019; 805–810. https://doi 10.1109/SII.2019.8700332
Manian, A. And Ronaghi, m. (2016). Providing a comprehensive framework for implementing Internet marketing using the meta-combined method. University of Tehran Press. 7 : 901-920. https://doi.10.22059/JIBM.2015.57097
Muraleedharan. K., (2008). Dynamics of People Participation in Development: A Study with Special Reference to Women Participation in the Local Level Planning in Kerala, Eldis Participation Resource Guide, Handbook of Cultural Geography, Sage, London.
Phupattanasilp, P., and Tong, S.R. (2016). Application of multiple view geometry for object positioning and inquiry in agricultural augmented reality. In Proceedings of the 2nd International Conference on Agricultural and
Biological Sciences, Shanghai, China, 23–26.
Primmer, E. and Kyllonen., S. (2008). Goals for Public Participation Implied by Sustainable Development and the Preparatory Process of the Finnish National Forest Program, Forest Policy and Economics, 8( 8): 838– 853. https://doi.org/10.1016/j.forpol.2005.01.002
Rashid, Z., Melià-Seguí, J., Pous, R., and Peig, E. (2017). Using Augmented Reality and Internet of Things to improve accessibility of people with motor disabilities in the context of Smart Cities. Future Gener. Comput. Syst. 76: 248–261. https://doi.org/10.1016/j.future.2016.11.030
Soma, K., Onwezen,M., Salverda, I.E., and I van Dam, R. (2016). Roles of citizens in environmental governance in the Information Age four theoretical perspectives. Current Opinion in Environmental Sustainability, 18: 122–130. https://doi.org/10.1016/j.cosust.2015.12.009
Sutherland, I.E. The Ultimate Display. In Proceedings of the IFIP Congress; Macmillan and Co.: London, UK,
1965; pp. 506–508. http://www.wired.com/beyond_the_beyond/2009/09/augmented-reality-the-ultimate-display-by-ivan-sutherland-1965/
Tati´c, D., and Teši´c, B. (2017). The application of augmented reality technologies for the improvement of occupational safety in an industrial environment. Comput. Ind. 85, 1–10. https://doi.org/10.1016/j.compind.2016.11.004
Teitel, M.A. (1990). The Eyephone: A head-mounted stereo display. In Stereoscopic Displays and Applications; SPIE: Bellingham, DC, USA, 1256: 168–171. https://doi.org/10.1117/12.19902
Todde G., Caria M., Gambella F., Pazzona A. (2017). Energy and Carbon Impact of Precision Livestock Farming Technologies Implementation in the Milk Chain: From Dairy Farm to Cheese Factory. Agriculture. 7:79. doi: 10.3390/agriculture7100079.
Tullo E., Finzi A., Guarino M. (2019). Environmental impact of livestock farming and Precision Livestock Farming as a mitigation strategy. Sci. Total Environ. 650: 2751–2760. doi: 10.1016/j.scitotenv.2018.10.018.
Todde G., Murgia L., Caria M., Pazzona A. (2016). A multivariate statistical analysis approach to characterize mechanization, structural and energy profile in Italian dairy farms. Energy Rep. 2: 129–134. doi: 10.1016/j.egyr.2016.05.006.
Wathes C.M., Kristensenb H.H., Aertsc J.M., Berckmans D. (2008). Is precision livestock farming an engineer’s daydream or nightmare, an animal’s friend or foe, and a farmer’s panacea or pitfall? Comput. Electron. Agric. 64: 2–10. doi: 10.1016/j.compag.2008.05.005.
Velázquez, F. and Morales Méndez, G. (2018). Augmented Reality and Mobile Devices: A Binominal Methodological Resource for Inclusive Education (SDG 4). An Example in Secondary Education. Sustainability 10: 34-46. DOI:10.3390/su10103446