Page 42 - AI Ready – Analysis Towards a Standardized Readiness Framework
P. 42
AI Ready – Analysis Towards a Standardized Readiness Framework
[16] Jabbari, A., Humayed, A., Reegu, F. A., Uddin, M., Gulzar, Y., & Majid, M. (2023). Smart
Farming Revolution: Farmer’s Perception and Adoption of Smart IoT Technologies for Crop
Health Monitoring and Yield Prediction in Jizan, Saudi Arabia. Sustainability, 15(19), Article 19.
https:// doi .org/ 10 .3390/ su151914541
[17] Jabbari, A., Teli, T. A., Masoodi, F., Reegu, F. A., Uddin, M., & Albakri, A. (2024). Prioritizing
factors for the adoption of IoT-based smart irrigation in Saudi Arabia: A GRA/AHP approach.
Frontiers in Agronomy, 6. https:// doi .org/ 10 .3389/ fagro .2024 .1335443
[18] Kashevnik, A., Shchedrin, R., Kaiser, C., & Stocker, A. (2021). Driver Distraction Detection
Methods: A Literature Review and Framework. IEEE Access, 9, 60063-60076. https:// doi .org/
10 .1109/ ACCESS .2021 .3073599
[19] Mansuri, F. (2015). Road safety and road traffic accidents in Saudi Arabia: Systematic review
of existing evidence. SMJ 2015; 36 (4). Saudi Medical Journal, 36.
[20] Muniasamy, A. (2020). Machine Learning for Smart Farming: A Focus on Desert Agriculture.
2020 International Conference on Computing and Information Technology (ICCIT-1441), 1-5.
https:// doi .org/ 10 .1109/ ICCIT -144147971 .2020 .9213759
[21] tinyML Foundation, https:// www .tinyml .org/
[22] oneM2M Sets Standards For The Internet Of Things & M2M, https:// www .onem2m .org/
[23] Prathiba, S. B., Raja, G., Dev, K., Kumar, N., & Guizani, M. (2021). A Hybrid Deep
Reinforcement Learning For Autonomous Vehicles Smart-Platooning. IEEE Transactions on
Vehicular Technology, 70(12), 13340-13350. https:// doi .org/ 10 .1109/ TVT .2021 .3122257
[24] Rezgui, J., Gagne, E., Blain, G., St-Pierre, O., & Harvey, M. (2020). Platooning of Autonomous
Vehicles with Artificial Intelligence V2I Communications and Navigation Algorithm. 2020 Global
Information Infrastructure and Networking Symposium (GIIS), 1-6. https:// doi .org/ 10 .1109/
GIIS50753 .2020 .9248490
[25] Sabet, M., Zoroofi, R. A., Sadeghniiat-Haghighi, K., & Sabbaghian, M. (2012). A new
system for driver drowsiness and distraction detection. 20th Iranian Conference on Electrical
Engineering (ICEE2012), 1247-1251. https:// doi .org/ 10 .1109/ IranianCEE .2012 .6292547
[26] Shajari, A., Asadi, H., Glaser, S., Arogbonlo, A., Mohamed, S., Kooijman, L., Abu Alqumsan,
A., & Nahavandi, S. (2023). Detection of Driving Distractions and Their Impacts. Journal of
Advanced Transportation, 2023, e2118553. https:// doi .org/ 10 .1155/ 2023/ 2118553
[27] James Agajo, Using AI to Reduce the 6G Standards Barrier for African Contributors,
available from ITU AI for Good-Innovate for Impact, Final Report 2024, https:// www .itu .int/ net/
epub/ TSB/ 2024 -AI -for -Good -Innovate -for -Impact -final -report/ index .html #p = 1
[28] Saher System, Kingdom of Saudi Arabia, https:// www .moi .gov .sa/ wps/ portal/ Home/
sectors/ publicsecurity/ traffic/ contents/ !ut/ p/ z0/ 04 _Sj9 CPykssy0xP LMnMz0vMAf Ijo8ziDTxN
TDwMTYy83V 0CTQ0cA71d _ T1djI0MXA3 0g1Pz9L30o _ArApqSmVV YGOWoH5Wcn
1eSWlGiH1F SlJiWlpmsa gBlKCQWqRr kJmbmqRoUJ 2akFukXZLuHAwCkY5qs/
[29] Trichias, K., Demestichas, P., & Mitrou, N. (2021). Inter-PLMN Mobility Management
Challenges for Supporting Cross-Border Connected and Automated Mobility (CAM) Over 5G.
Journal of ICT Standardization, 113-146. https:// doi .org/ 10 .13052/ jicts2245 -800X .924
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