Titre : |
Artificial intelligence and conservation |
Type de document : |
texte imprimé |
Auteurs : |
Fei Fang, Éditeur scientifique |
Editeur : |
Cambridge : Cambridge University Press |
Année de publication : |
2019 |
Collection : |
Artificial intelligence for social good |
Importance : |
X, 236 p. |
Présentation : |
ill. |
Format : |
23 cm |
ISBN/ISSN/EAN : |
978-1-108-46473-4 |
Note générale : |
Références bibliographiques. - Glossaire. - Index |
Langues : |
Anglais (eng) |
Mots-clés : |
Artificial intelligence
Intelligence artificielle |
Index. décimale : |
004.383.8 Intelligence artificielle |
Résumé : |
With the increasing public interest in artificial intelligence (AI), there is also increasing interest in learning about the benefits that AI can deliver to society. This book focuses on research advances in AI that benefit the conservation of wildlife, forests, coral reefs, rivers, and other natural resources. It presents how the joint efforts of researchers in computer science, ecology, economics, and psychology help address the goals of the United Nations' 2030 Agenda for Sustainable Development. Written at a level accessible to conservation professionals and AI researchers, the book offers both an overview of the field and an in-depth view of how AI is being used to understand patterns in wildlife poaching and enhance patrol efforts in response, covering research advances, field tests and real-world deployments. The book also features efforts in other major conservation directions, including protecting natural resources, ecosystem monitoring, and bio-invasion management through the use of game theory, machine learning, and optimization. |
Note de contenu : |
Au sommaire :
1. Introduction
Part I.
2 - Law Enforcement for Wildlife Conservation
3 - Wildlife Poaching Forecasting Based on Ranger–Collected Data and Evaluation through Field Tests
4 - Optimal Patrol Planning Against Black-Box Attackers
5 - Automatic Detection of Poachers and Wildlife with UAVs
Part II
6 - Protecting Coral Reef Ecosystems via Efficient Patrols
7 - Simultaneous Optimization of Strategic and Tactical Planning for Environmental Sustainability and Securitypp
8 - NECTAR: Enforcing Environmental Compliance through Strategically Randomized Factory Inspections
9 - Connecting Conservation Research and Implementation: Building aWildfire Assistant
10 - Probabilistic Inference with Generating Functions for Animal Populations
11 - Engaging Citizen Scientists in Data Collection for Conservation
12 - Simulator-Defined Markov Decision Processes: A Case Study in Managing Bio-invasions |
Artificial intelligence and conservation [texte imprimé] / Fei Fang, Éditeur scientifique . - Cambridge : Cambridge University Press, 2019 . - X, 236 p. : ill. ; 23 cm. - ( Artificial intelligence for social good) . ISBN : 978-1-108-46473-4 Références bibliographiques. - Glossaire. - Index Langues : Anglais ( eng)
Mots-clés : |
Artificial intelligence
Intelligence artificielle |
Index. décimale : |
004.383.8 Intelligence artificielle |
Résumé : |
With the increasing public interest in artificial intelligence (AI), there is also increasing interest in learning about the benefits that AI can deliver to society. This book focuses on research advances in AI that benefit the conservation of wildlife, forests, coral reefs, rivers, and other natural resources. It presents how the joint efforts of researchers in computer science, ecology, economics, and psychology help address the goals of the United Nations' 2030 Agenda for Sustainable Development. Written at a level accessible to conservation professionals and AI researchers, the book offers both an overview of the field and an in-depth view of how AI is being used to understand patterns in wildlife poaching and enhance patrol efforts in response, covering research advances, field tests and real-world deployments. The book also features efforts in other major conservation directions, including protecting natural resources, ecosystem monitoring, and bio-invasion management through the use of game theory, machine learning, and optimization. |
Note de contenu : |
Au sommaire :
1. Introduction
Part I.
2 - Law Enforcement for Wildlife Conservation
3 - Wildlife Poaching Forecasting Based on Ranger–Collected Data and Evaluation through Field Tests
4 - Optimal Patrol Planning Against Black-Box Attackers
5 - Automatic Detection of Poachers and Wildlife with UAVs
Part II
6 - Protecting Coral Reef Ecosystems via Efficient Patrols
7 - Simultaneous Optimization of Strategic and Tactical Planning for Environmental Sustainability and Securitypp
8 - NECTAR: Enforcing Environmental Compliance through Strategically Randomized Factory Inspections
9 - Connecting Conservation Research and Implementation: Building aWildfire Assistant
10 - Probabilistic Inference with Generating Functions for Animal Populations
11 - Engaging Citizen Scientists in Data Collection for Conservation
12 - Simulator-Defined Markov Decision Processes: A Case Study in Managing Bio-invasions |
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