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AI Ready – Analysis Towards a Standardized Readiness Framework



                  7      Reference


                  [1] Zhanmei Zhang, Computer Network Fusion Video Brain, 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

                  [2] Mengzhu Li, Smartphone OS-based Information Accessibility Solutions and Public Welfare
                  for People with Disabilities, 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
                  [3] Open Data Platform, Kingdom of Saudi Arabia, Datasets provided to the public to enhance
                  access to information, collaboration, and innovation https:// open .data .gov .sa/ en/ home

                  [4] AI for Road Safety Global Initiative, https:// www .itu .int: 443/ en/ ITU -T/ ITS/ AIRoadSafety/
                  Pages/ default .aspx

                  [5] Aljohani, Abeer. A. (2023). Real-time driver distraction recognition: A hybrid genetic deep
                  network based approach. Alexandria Engineering Journal, 66, 377-389. https:// doi .org/ 10
                        j
                  .1016/  .aej .2022 .12 .009
                  [6] Al-Shammari, H., & Ling, C. (2019). Investigating the Effectiveness of a Traffic Enforcement
                  Camera-System on the Road Safety in Saudi Arabia (pp. 660-670). https:// doi .org/ 10 .1007/
                  978 -3 -319 -93885 -1 _60

                  [7] Alsuwian, T., Saeed, R. B., & Amin, A. A. (2022). Autonomous Vehicle with Emergency
                  Braking Algorithm Based on Multi-Sensor Fusion and Super Twisting Speed Controller. Applied
                  Sciences, 12(17), Article 17. https:// doi .org/ 10 .3390/ app12178458

                  [8] Chen, Y., Xue, M., Zhang, J., Ou, R., Zhang, Q., & Kuang, P. (2022). DetectDUI: An In-Car
                  Detection System for Drink Driving and BACs. IEEE/ACM Transactions on Networking, 30(2),
                  896–910. https:// doi .org/ 10 .1109/ TNET .2021 .3125950

                  [9] Collaboration on ITS Communication Standards, https:// www .itu .int: 443/ en/ ITU -T/ extcoop/
                  cits/ Pages/ default .aspx

                  [10] Dai, J., Teng, J., Bai, X., Shen, Z., & Xuan, D. (2010). Mobile phone based drunk driving
                  detection. 2010 4th International Conference on Pervasive Computing Technologies for
                  Healthcare, 1-8. https:// doi .org/ 10 .4108/ ICST .PERVASIVEHEALTH2010 .8901

                  [11] Edge Impulse – The Leading edge AI platform, https:// edgeimpulse .com/

                  [12] Distracted Driver Dataset, http:// heshameraqi .github .io/ distraction _detection

                  [13] Find Open Datasets and Machine Learning Projects | Kaggle. https:// www .kaggle .com/
                  datasets

                  [14] ICT in Agriculture (Updated Edition),  https:// www .fao .org/ family -farming/ detail/ fr/ c/
                  1028927/

                  [15] Ingress Protection (IP) ratings, https:// www .iec .ch/ ip -ratings







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