Skip to content
1981
Volume 24, Issue 3
  • ISSN: 1474-2748
  • E-ISSN: 2040-0551

Abstract

This article explores the role of Artificial Intelligence of Things (AIoT) in sustainable development, highlighting its potential to address global challenges and contribute to the achievement of the United Nations’ Sustainable Development Goals. AIoT combines AI with the Internet of Things, enhancing sustainable development by improving supply chain and transportation efficiency, reducing costs and fostering trust among partners. It also supports the development of sustainable rail transit systems, optimizes traffic control and facilitates autonomous driving. AIoT further streamlines manufacturing processes, increasing efficiency and minimizing waste. The study examines AIoT from academic, domain and industry-specific perspectives. AIoT systems face challenges related to data security, privacy, GDPR compliance, interoperability, financial investment and sustainability. Future research should focus on robust security protocols, energy-efficient hardware and renewable energy sources, requiring collaboration among academia, industry and government.

© 2025 Intellect Ltd
Loading

Article metrics loading...

/content/journals/10.1386/tmsd_00110_1
2025-12-22
2026-04-22

Metrics

Loading full text...

Full text loading...

References

  1. Adli, H. K., Remli, M. A., Wan Salihin Wong, K. N. S., Ismail, N. A., González-Briones, A., Corchado, J. M. and Mohamad, M. S. (2023), ‘Recent advancements and challenges of AIoT application in smart agriculture: A review’, Sensors, 23:7, https://doi.org/10.3390/s23073752.
     [Google Scholar]
  2. Ahmed, K., Verma, K., Dubey, M. K. and Pandey, D. K. (2024), ‘User-friendly AIoT Enabled Walnut Recommendation System (UAWCRS): Concept and architecture’, Second International Conference on Advanced Computing & Communication Technologies (ICACCTech), Delhi-NCR, India, 16–17 November, https://api.semanticscholar.org/CorpusID:276993441. Accessed 4 October 2025.
     [Google Scholar]
  3. Ahvar, E., Ahvar, S. and Lee, G. M. (2024), ‘Artificial intelligence of things: Architectures, applications, and challenges’, in S. Ziegler, R. Radócz, A. Quesada Rodriguez and S. N. Matheu Garcia (eds), Springer Handbook of Internet of Things, Cham: Springer, pp. 443–62.
     [Google Scholar]
  4. Alaba, F. A., Sani, U., Dada, E. G. and Mohammed, B. H. (2024), ‘AIoT-enabled smart grids: Advancing energy efficiency and renewable energy integration’, in S. Misra, K. Siakis and G. Lampropoulos (eds), Artificial Intelligence of Things for Achieving Sustainable Development Goals, Cham: Springer, pp. 59–79.
     [Google Scholar]
  5. Alakkari, K. and Ali, B. (2025), ‘Artificial intelligence of things: A review’, Babylonian Journal of Internet of Things, pp. 113–20, https://doi.org/10.58496/bjiot/2025/006.
     [Google Scholar]
  6. Aliahmadi, A., Nozari, H. and Ghahremani-Nahr, J. (2022a), ‘A framework for IoT and blockchain based on marketing systems with an emphasis on big data analysis’, International Journal of Innovation in Marketing Elements, 2:1, pp. 25–34, https://doi.org/10.59615/ijime.2.1.25.
     [Google Scholar]
  7. Aliahmadi, A., Nozari, H. and Ghahremani-Nahr, J. (2022b), ‘AIoT-based sustainable smart supply chain framework’, International Journal of Innovation in Management, Economics and Social Sciences, 2:2, pp. 28–38, https://doi.org/10.52547/ijimes.2.2.28.
     [Google Scholar]
  8. Aliahmadi, A., Nozari, H., GhahremaniNahr, J. and SzmelterJarosz, A. (2022c), ‘Evaluation of key impression of resilient supply chain based on AIoT using a nonlinear fuzzy method’, Journal of Fuzzy Extension and Applications, 3:3, pp. 201–11, https://doi.org/10.22105/jfea.2022.345008.1221.
     [Google Scholar]
  9. Amatya, S., Karkee, M., Gongal, A., Zhang, Q. and Whiting, M. D. (2016), ‘Detection of cherry tree branches with full foliage in planar architecture for automated sweet-cherry harvesting’, Biosystems Engineering, 146, pp. 3–15, https://doi.org/10.1016/j.biosystemseng.2015.10.003.
     [Google Scholar]
  10. Anagnostopoulos, C., Gkillas, A., Mavrokefalidis, C., Pikoulis, E. V., Piperigkos, N. and Lalos, A. S. (2024), ‘Multimodal federated learning in AIoT systems: Existing solutions, applications, and challenges’, IEEE Access, 12, pp. 180864–902, https://doi.org/10.1109/access.2024.3508030.
     [Google Scholar]
  11. Bacco, M., Berton, A., Ferro, E., Gennaro, C., Gotta, A., Matteoli, S., Paonessa, F., Ruggeri, M., Virone, G. and Zanella, A. (2018), ‘Smart farming: Opportunities, challenges, and technology enablers’, 2018 IoT Vertical and Topical Summit on Agriculture – Tuscany (IOT Tuscany), Tuscany, Italy, 8–9 May, Institute of Electrical and Electronics Engineers (IEEE), pp. 1–6.
     [Google Scholar]
  12. Baker, S. and Xiang, W. (2023), ‘Artificial intelligence of things for smarter healthcare: A survey of advancements, challenges, and opportunities’, IEEE Communications Surveys & Tutorials, 25:2, pp. 1261–93, https://doi.org/10.1109/comst.2023.3256323.
     [Google Scholar]
  13. Bibri, S. E. and Jagatheesaperumal, S. K. (2023), ‘Harnessing the potential of the metaverse and artificial intelligence for the internet of city things: Cost-effective XReality and synergistic AIoT technologies’, Smart Cities, 6:5, pp. 2397–429, https://doi.org/10.3390/smartcities6050109.
     [Google Scholar]
  14. Boulouard, Z., Ouaissa, M., Ouaissa, M. and El Himer, S. (2022), AI and IoT for Sustainable Development in Emerging Countries, Cham: Springer.
     [Google Scholar]
  15. Bronner, W., Gebauer, H., Lamprecht, C. and Wortmann, F. (2021), ‘Sustainable AIoT: How artificial intelligence and the Internet of Things affect profit, people, and planet’, in O. Gassmann and F. Ferrandina (eds), Connected Business, Cham: Springer, pp. 137–54.
     [Google Scholar]
  16. Cavalcante, I. M., Frazzon, E. M., Forcellini, F. A. and Ivanov, D. (2019), ‘A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing’, International Journal of Information Management, 49, pp. 86–97, https://doi.org/10.1016/j.ijinfomgt.2019.03.004.
     [Google Scholar]
  17. Chang, Z., Liu, S., Xiong, X., Cai, Z. and Tu, G. (2021), ‘A survey of recent advances in edge-computing-powered artificial intelligence of things’, IEEE Internet of Things Journal, 8:18, pp. 13849–75, https://doi.org/10.1109/jiot.2021.3088875.
     [Google Scholar]
  18. Chen, S.-W., Gu, X.-W., Wang, J.-J. and Zhu, H.-S. (2021), ‘AIoT used for COVID-19 pandemic prevention and control’, Contrast Media & Molecular Imaging, pp. 1–23, https://doi.org/10.1155/2021/3257035.
     [Google Scholar]
  19. Chookaew, S., Kitcharoen, P., Howimanporn, S. and Panjaburee, P. (2024), ‘Fostering student competencies and perceptions through an artificial intelligence of things educational platform’, Computers and Education: Artificial Intelligence, 7, https://doi.org/10.1016/j.caeai.2024.100308.
     [Google Scholar]
  20. Colglazier, W. (2015), ‘Sustainable development agenda: 2030’, Science, 349:6252, pp. 1048–50, https://doi.org/10.1126/science.aad2333.
     [Google Scholar]
  21. Corchado Rodríguez, J. M. (2021), ‘AIoT for achieving sustainable development goals’, 4th International Conference on Recent Trends in Advanced Computing, Chennai, India, 11–12 November, https://ep00.epimg.net/infografias/2024/04/corchado/Corchado%20Chennai.pdf. Accessed 4 October 2025.
  22. Diesendorf, M. (2001), ‘Models of sustainability and sustainable development’, International Journal of Agricultural Resources, Governance and Ecology, 1:2, p. 109, https://doi.org/10.1504/ijarge.2001.000007.
     [Google Scholar]
  23. Dong, B., Shi, Q., Yang, Y., Wen, F., Zhang, Z. and Lee, C. (2021), ‘Evolution of technology from self-powered sensors to AIoT-enabled smart homes’, Nano Energy, 79, https://doi.org/10.1016/j.nanoen.2020.105414.
     [Google Scholar]
  24. El Himer, S., Ouaissa, M., Ouaissa, M. and Boulouard, Z. (2022), ‘Artificial Intelligence of Things (AIoT) for renewable energies systems’, in S. El Himer, M. Ouaissa, A. A. A. Emhemed, M. Ouaissa and Z. Boulouard (eds), Artificial Intelligence of Things for Smart Green Energy Management, Cham: Springer, pp. 1–13.
     [Google Scholar]
  25. Elijah, O., Abioye, A. E. and Maguvu, T. E. (2024), ‘Pest and disease management in ginger plants: Artificial Intelligence of Things (AIoT)’, IEEE Transactions on AgriFood Electronics, 3:1, pp. 86–97, https://doi.org/10.1109/tafe.2024.3492323.
     [Google Scholar]
  26. Firouzi, F., Jiang, S., Chakrabarty, K., Farahani, B., Daneshmand, M., Song, J. and Mankodiya, K. (2022), ‘Fusion of IoT, AI, edge–fog–cloud, and blockchain: Challenges, solutions, and a case study in healthcare and medicine’, IEEE Internet of Things Journal, 10:5, pp. 3686–705, https://doi.org/10.1109/jiot.2022.3191881.
     [Google Scholar]
  27. Florea, A. (2024), ‘The emerging technologies: The drivers for digital transformation in business and education’, International Journal of Advanced Statistics and IT&C for Economics and Life Sciences, 14:1, pp. 213–21, https://doi.org/10.2478/ijasitels-2024-0019.
     [Google Scholar]
  28. Fraga-Lamas, P., Lopes, S. I. and Fernández-Caramés, T. M. (2021), ‘Green IoT and edge AI as key technological enablers for a sustainable digital transition toward a smart circular economy: An Industry 4.0 use case’, Sensors, 21:17, p. 5745, https://doi.org/10.3390/s21175745.
     [Google Scholar]
  29. Ghoreishi, M., Treves, L. and Kuivalainen, O. (2022), ‘Artificial intelligence of things as an accelerator of the circular economy in international business’, in S. Batas, O. Kuivalainen and R. R. Sinkovics (eds), Megatrends in International Business, Cham: Springer, pp. 83–104.
     [Google Scholar]
  30. Haroun, A., Le, X., Gao, S., Dong, B., He, T., Zhang, Z., Wen, F., Xu, S. and Lee, C. (2021), ‘Progress in micro/nano sensors and nano energy for future AIoT-based smart home applications’, Nano Express, 2:2, https://doi.org/10.1088/2632-959x/abf3d4.
     [Google Scholar]
  31. Hussain, A. and Qureshi, K. N. (2024), ‘Standards and policies adoption for AIoT networks’, in K. N. Qureshi and T. Newe (eds), Artificial Intelligence of Things (AIoT): New Standards, Technologies and Communication Systems, Boca Raton, FL: CRC Press, pp. 49–76.
     [Google Scholar]
  32. Ibrahim, H. T., Mazher, W. J. and Ucan, O. N. (2022), ‘AIoT in healthcare: A systematic mapping study’, in Nişantaşi University (eds), 2022 International Conference on Artificial Intelligence of Things (ICAIoT), Istanbul, Turkey, 29–30 December, IEEE, pp. 1–6.
     [Google Scholar]
  33. Kang, H. C., Lim, S. K., Lee, Y., Kim, M. G. and Son, J. Y. (2024), ‘Cost-effective AIoT-based hazard detection using 2D cameras in manufacturing environments’, The International Journal of Advanced Manufacturing Technology, 135:9, pp. 1–14, https://doi.org/10.1007/s00170-024-14783-2.
     [Google Scholar]
  34. Kansal, N., Bhushan, B. and Sharma, S. (2022), ‘Architecture, security vulnerabilities, and the proposed countermeasures in Agriculture-Internet-of-Things (AIoT) systems’, in P. K. Pattnaik, R. Kumar and S. Pal (eds), Internet of Things and Analytics for Agriculture, Cham: Springer, pp. 329–53.
     [Google Scholar]
  35. Kono, N. (2020), ‘Brundtland Commission (World Commission on Environment and Development)’, in F. Maggino (ed.), Encyclopedia of Quality of Life and Well-Being Research, Cham: Springer, pp. 1–3, https://doi.org/10.1007/978-3-319-69909-7_441-2.
     [Google Scholar]
  36. Lampropoulos, G., Garzón, J., Misra, S. and Siakas, K. (2024), ‘The role of artificial intelligence of things in achieving sustainable development goals: State of the art’, Sensors, 24:4, https://doi.org/10.3390/s24041091.
     [Google Scholar]
  37. Lee, B. X., Kjaerulf, F., Turner, S., Cohen, L., Donnelly, P. D., Muggah, R. and Gilligan, J. (2016), ‘Transforming our world: Implementing the 2030 agenda through sustainable development goal indicators’, Journal of Public Health Policy, 37 (Supp 1), pp. 13–31, https://doi.org/10.1057/s41271-016-0002-7.
     [Google Scholar]
  38. Machado, C. G., Winroth, M. P. and Ribeiro Da Silva, E. H. D. (2020), ‘Sustainable manufacturing in Industry 4.0: An emerging research agenda’, International Journal of Production Research, 58:5, pp. 1462–84, https://doi.org/10.1080/00207543.2019.1652777.
     [Google Scholar]
  39. Marinova, N. (2024), ‘Advantages and ethical considerations of industrial IoT artificial intelligence solutions usage’, Business Management, 2, pp. 43–58, https://doi.org/10.58861/tae.bm.2024.2.03.
     [Google Scholar]
  40. Matin, A., Islam, M. R., Wang, X., Huo, H. and Xu, G. (2023), ‘AIoT for sustainable manufacturing: Overview, challenges, and opportunities’, Internet of Things, 24, https://doi.org/10.1016/j.iot.2023.100901.
     [Google Scholar]
  41. Misra, S. (2024), Artificial Intelligence of Things for Achieving Sustainable Development Goals, Cham: Springer.
     [Google Scholar]
  42. Muhammed, D., Ahvar, E., Ahvar, S., Trocan, M., Montpetit, M.-J. and Ehsani, R. (2024), ‘Artificial Intelligence of Things (AIoT) for smart agriculture: A review of architectures, technologies, and solutions’, Journal of Network and Computer Applications, 228, https://doi.org/10.1016/j.jnca.2024.103905.
     [Google Scholar]
  43. Nahr, J. G., Nozari, H. and Sadeghi, M. E. (2021), ‘Green supply chain based on artificial intelligence of things (AIoT)’, International Journal of Innovation in Management, Economics and Social Sciences, 1:2, https://doi.org/10.52547/ijimes.1.2.56.
     [Google Scholar]
  44. Nishimura, E. H., Iano, Y., de Oliveira, G. G. and Vaz, G. C. (2022), ‘Application and requirements of AIoT-enabled industrial control units’, in Y. Iano, O. Saotome, G. L. Kemper Vásquez, C. Cotrim Pezzuto, R. Arthur and G. Gomes de Oliveira (eds), Proceedings of the 7th Brazilian Technology Symposium (BTSym’21), Cham: Springer, pp. 724–33.
     [Google Scholar]
  45. Nozari, H., Fallah, M. and Szmelter-Jarosz, A. (2021), ‘A conceptual framework of green smart IoT-based supply chain management’, International Journal of Research in Industrial Engineering, 10:1, pp. 22–34, https://doi.org/10.22105/RIEJ.2021.274859.1189.
     [Google Scholar]
  46. Nozari, H., Rahmaty, M. and Szmelter-Jarosz, A. (2024), ‘A framework for AIoT-based smart, sustainable marketing system’, in S. Misra, K. Siakis and G. Lampropoulos (eds), Artificial Intelligence of Things for Achieving Sustainable Development Goals, Cham: Springer, pp. 255–71.
     [Google Scholar]
  47. Pappakrishnan, V., Mythili, R., Kavitha, V. and Parthiban, N. (2021), ‘Role of Artificial Intelligence of Things (AIoT) in COVID-19 pandemic: A brief survey’, in Proceedings of the 6th International Conference on Internet of Things, Big Data and Security, online streaming, 23–25 April, Lisbon: INSTICC, pp. 229–36.
     [Google Scholar]
  48. Parris, T. M. and Kates, R. W. (2003), ‘Characterising and measuring sustainable development’, Annual Review of Environment and Resources, 28:1, pp. 559–86, https://doi.org/10.1146/annurev.energy.28.050302.105551.
     [Google Scholar]
  49. Pathak, D., Rathod, V. and Chapaneri, R. (2023), ‘A comprehensive survey on AIoT-integrated smart health cities’, in AIP Conference Proceedings, 2705:1, p. 40004, https://doi.org/10.1063/5.0133615.
     [Google Scholar]
  50. Pise, A., Yoon, B. and Singh, S. (2023), ‘Enabling Ambient Intelligence of Things (AIoT) healthcare system architectures’, Computer Communications, 198, pp. 186–94, https://doi.org/10.1016/j.comcom.2022.10.029.
     [Google Scholar]
  51. Rajamohan, K., Rangasamy, S., Baby, L., Niveditha, G. and Muktha, D. S. (2024), ‘Agricultural Internet of Things (AIoT): Architecture, applications, and challenges’, in A. Khang, V. Abdullayev, V. Hahanov and V. Shah (eds), Advanced IoT Technologies and Applications in the Industry 4.0 Digital Economy, Boca Raton, FL: CRC Press, pp. 349–73.
     [Google Scholar]
  52. Revathi, A. and Poonguzhali, S. (2023), ‘The role of AIoT-based automation systems using UAVs in smart agriculture’, in D. U. Mishra and S. Sharma (eds), Revolutionising Industrial Automation through the Convergence of Artificial Intelligence and the Internet of Things, Hershey, PA: IGI Global, pp. 100–17.
     [Google Scholar]
  53. Rupanetti, D. and Kaabouch, N. (2024), ‘Combining edge computing-assisted internet of things security with artificial intelligence: Applications, challenges, and opportunities’, Applied Sciences, 14:16, n.pag., https://doi.org/10.3390/app14167104.
     [Google Scholar]
  54. Seng, K. P., Ang, L. M. and Ngharamike, E. (2022), ‘Artificial intelligence Internet of Things: A new paradigm of distributed sensor networks’, International Journal of Distributed Sensor Networks, 18:3, n.pag., https://doi.org/10.1177/15501477211062835.
     [Google Scholar]
  55. Shi, Q., Yang, Y., Sun, Z. and Lee, C. (2022), ‘Progress of advanced devices and internet of things systems as enabling technologies for smart homes and health care’, ACS Materials Au, 2:4, pp. 394–435, https://doi.org/10.1021/acsmaterialsau.2c00001.
     [Google Scholar]
  56. Singha, R. and Singha, S. (2024), ‘AIoT concepts and integration: Exploring customer interaction, ethics, policy, and privacy’, in S. Rezaei and A. Ansary (eds), Artificial Intelligence of Things (AIoT) for Productivity and Organisational Transition, Hershey, PA: IGI Global, pp. 26–51.
     [Google Scholar]
  57. Slama, D., Rückert, T., Thrun, S., Homann, U. and Lasi, H. (eds) (2023), The Digital Playbook: A Practitioner’s Guide to Smart, Connected Products and Solutions with AIoT, Cham: Springer.
     [Google Scholar]
  58. Srikonda, R. Rastogi, A. and Oestensen, H. (2020), ‘Increasing facility uptime using machine learning and physics-based hybrid analytics in a dynamic digital twin’, Offshore Technology Conference, Houston, TX, USA, 17–19 August, Houston, TX: Offshore Technology Conference (OTC), p. D031S032R002.
     [Google Scholar]
  59. Talukder, A. and Haas, R. (2021), ‘AIoT: AI meets IoT and web in smart healthcare’, in Companion Publication of the 13th ACM Web Science Conference 2021, New York, USA, 21–25 June, New York: Association for Computing Machinery (ACM), pp. 92–98.
     [Google Scholar]
  60. Tang, H., Kong, L., Fang, Z., Zhang, Z., Zhou, J., Chen, H. and Zou, X. (2024), ‘Sustainable and innovative rail transit based on advanced self-powered sensing technology’, iScience, 27:12, https://doi.org/10.1016/j.isci.2024.111306.
     [Google Scholar]
  61. Thiele, L. P. (2024), Sustainability, Chichester: Wiley.
     [Google Scholar]
  62. Tsalis, T. A., Malamateniou, K. E., Koulouriotis, D. and Nikolaou, I. E. (2020), ‘New challenges for corporate sustainability reporting: United Nations’ 2030 Agenda for sustainable development and the sustainable development goals’, Corporate Social Responsibility and Environmental Management, 27:4, pp. 1617–29, https://doi.org/10.1002/csr.1910.
     [Google Scholar]
  63. United Nations (2021), ‘Progress towards the Sustainable Development Goals Report of the Secretary-General’, E/2021/58, New York: United Nations (UN), https://undocs.org/Home/Mobile?FinalSymbol=E2F20212F58&Language=E&DeviceType=Desktop&LangRequested=False. Accessed 31 December 2024.
     [Google Scholar]
  64. Van Marrewijk, M. and Werre, M. (2003), ‘Multiple levels of corporate sustainability’, Journal of Business Ethics, 44:2–3, pp. 107–19, https://doi.org/10.1023/a:1023383229086.
     [Google Scholar]
  65. Walia, G. K., Kumar, M. and Gill, S. S. (2023), ‘AI-empowered fog/edge resource management for IoT applications: A comprehensive review, research challenges, and future perspectives’, IEEE Communications Surveys & Tutorials, 26:1, pp. 619–69, https://doi.org/10.1109/comst.2023.3338015.
     [Google Scholar]
  66. Wang, R. J., Yu, W. D., Liao, H. C., Chang, H. K. and Lim, Z. Y. (2024), ‘Cost/benefit analysis of AIoT image sensing for construction safety monitoring’, Journal of Engineering, Project & Production Management, 14:3, pp. 1–13, https://doi.org/10.32738/JEPPM-2024-0022.
     [Google Scholar]
  67. Wei, X., Zhang, J., Lyulyov, O. and Pimonenko, T. (2023), ‘The role of digital economy in enhancing the sports industry to attain sustainable development’, Sustainability, 15:15, https://doi.org/10.3390/su151512009.
     [Google Scholar]
  68. Xu, H., Seng, K. P., Ang, L. M. and Smith, J. (2024), ‘Decentralised and distributed learning for AIoT: A comprehensive review, emerging challenges and opportunities’, IEEE Access, 12, pp. 101016–52, https://doi.org/10.1109/access.2024.3422211.
     [Google Scholar]
  69. Yang, C.-T., Chen, H.-W., Chang, E.-J., Kristiani, E., Nguyen, K. L. P. and Chang, J.-S. (2021), ‘Current advances and future challenges of AIoT applications in particulate matter (PM) monitoring and control’, Journal of Hazardous Materials, 419, https://doi.org/10.1016/j.jhazmat.2021.126442.
     [Google Scholar]
  70. Yu, H., Han, S., Yang, D., Wang, Z. and Feng, W. (2021), ‘Job shop scheduling based on digital twin technology: A survey and an intelligent platform’, Complexity, 1, https://doi.org/10.1155/2021/8823273.
     [Google Scholar]
  71. Zaid, Y., Cavus, N., Omonayajo, B., Sekeroglu, B. and Al-Turjman, F. (2021), ‘Deep learning in mobile devices and the blockchain era: An overview’, 2021 International Conference on Forthcoming Networks and Sustainability in AIoT Era (FoNeS-AIoT), Nicosia, Turkey, 27–28 December.
  72. Zhang, J. and Tao, D. (2021a), ‘Empowering things with intelligence: A survey of the progress, challenges, and opportunities in artificial intelligence of things’, IEEE Internet of Things Journal, 24:10, pp. 7789–817, https://doi.org/10.1109/jiot.2020.3039359.
     [Google Scholar]
  73. Zhang, X., Hu, M., Xia, J., Wei, T., Chen, M. and Hu, S. (2020), ‘Efficient federated learning for cloud-based AIoT applications’, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 40:11, pp. 2211–23, https://doi.org/10.1109/tcad.2020.3046665.
     [Google Scholar]
  74. Zhang, X., Shu, K., Rajkumar, S. A. and Sivakumar, V. (2021b), ‘Research on the deep integration of the application of artificial intelligence in environmental monitoring systems and the real economy’, Environmental Impact Assessment Review, 86:1, https://doi.org/10.1016/j.eiar.2020.106499.
     [Google Scholar]
/content/journals/10.1386/tmsd_00110_1
Loading
Artificial Intelligence of Things: A review of its potential for sustainability
International Journal of Technology Management & Sustainable Development 24, 361 (2025); https://doi.org/10.1386/tmsd_00110_1
/content/journals/10.1386/tmsd_00110_1
/content/journals/10.1386/tmsd_00110_1
Loading

Data & Media loading...

  • Article Type: Article
Keyword(s): AIoT ethical considerations; application domains; industry case studies; sustainability challenges; Sustainable Development Goals (SDGs); technical implementations

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a success
Invalid data
An error occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test