"Our Intelligent Arctic Vision: 2025-2040" - Extended Version
DrDavidProbert
55 views
150 slides
Jul 29, 2024
Slide 1 of 150
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
About This Presentation
The presentation reviews potential practical applications of the emerging field of Artificial Intelligence (AI) to monitor & manage our arctic environmental assets & resources.
(1) Personal Background: In June 1992 I first visited INEP/KSC & together with colleagues established the Inte...
The presentation reviews potential practical applications of the emerging field of Artificial Intelligence (AI) to monitor & manage our arctic environmental assets & resources.
(1) Personal Background: In June 1992 I first visited INEP/KSC & together with colleagues established the International KolaNet Programme for Environmental Monitoring using contemporary computer networking technologies including the Internet & Web Servers. For the 35th INEP Anniversary I review practical ways to apply AI to the challenges of arctic monitoring & consider a short-list of research & operational projects for the next 15 years.
(2) Past Event Timeline: Birth of Computer Networking & Intelligence. The early pioneers of Statistical Learning included 18thC Thomas Bayes (1702-1761) who established Bayesian Learning that is now used extensively in Intelligent Cybersecurity & Advanced Machine Learning. Modern AI & Computing emerged 80 years ago in the early 1940s with the mathematical creation of Neural Networks & the first electronic computers such as “Colossus” at Dollis Hill, UK. In 1973, already 50 years ago, I started by own PhD research into “Stochastic Machine Learning” & “Self-Organising Systems” at Cambridge University, UK
(3) Present Day Research: Physical & Human Arctic Environment & Cyber Tech Support. There are already extensive applications of Big Data Mining, AI & Machine Learning and Real-Time Image & Sensor Surveillance within Arctic Scientific Research. The multi-dimensional environments researched include Water Resources & Living Organisms, Air Pollution & Meteorology, Human Activities, Towns & Industrial Enterprises, Terrestrial Organic Life including Plants, Forests & Animals, Arctic Transportation & Geological Surveys.
(4) Future Vision 2025-2040: Practical Applications of AI & Machine Learning. We can consider the Arctic in both Physical Geographical Space as well as Temporal Events from Micro to Macro. I suggest that the ultimate aim of AI research tools is to establish a “Smart” or “Intelligent” Arctic that is to some extent able to self-monitor & triage alerts such as heavy metal water contamination, seismic events, chemical air pollution or possible radiation leaks. The Arctic Environment is so extensive in both Space & Time that during the coming 15+ years, AI will become an essential tool to monitor & apply the massive real-time data from the expanding network of active arctic sensors. It is already clear that AI will be of considerable use in the practical analysis of climate change, and long term assessment of arctic sea ice. Further applications of AI may be into the impact of industrial & geological enterprises within the dynamic arctic eco-system. Eventually we may expect that all aspects of Our Arctic Environments maybe explored in quasi-real-time through networked sensors & alerts triaged through AI Tools & Human Intelligence into an innovative “Arctic Digital Twin”!