Page 45 - AI Ready – Analysis Towards a Standardized Readiness Framework

AI Ready – Analysis Towards a Standardized Readiness Framework

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[60] Siti Nur Aisyah Mohd Robi, Norulhusna Ahmad, Mohd Azri Mohd Izhar, Hazilah Mad Kaidi
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[61] OMACS, “Digital twins for AI based xapps in open RAN for smart agriculture in 5G”, available
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[62] ITU-T Recommendation, Y.3179 : Architectural framework for machine learning model
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[63] ITU-T Recommendation, Y.3172 : Architectural framework for machine learning in future
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[64] ITU-T Recommendation, Y.3181 : Architectural framework for machine learning sandbox
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[65] CSEM, Aurora weather stations dataset, https:// aurora .portal .csem .ch/ dataset .html

[66] ITU AI for Good TinyML Challenge “Next-Gen tinyML Smart Weather Station Challenge
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[67] Next-Gen tinyML Smart Weather Station Challenge 2024 Report, https:// github .com/ ITU
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[69] “Notun Kuri” Mobile Application, Notun Kuri (notun-kuri.netlify.app)

[70] ITU AI for Good-Innovate for Impact, Final Report 2024, https:// www .itu .int/ net/ epub/ TSB/
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[71] Ahmed, Z., Gui, D., murtaza, G., Yunfei, L., & Ali, S. (2023, August 11). An Overview of Smart
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[72] Dr. Dimple, & Rajput, j. (2023, july). Efficient Irrigation Water Management Tools and
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