Ahmad, 2024 - Google Patents
Smart remote sensing network for disaster management: an overviewAhmad, 2024
- Document ID
- 11921670373413255477
- Author
- Ahmad R
- Publication year
- Publication venue
- Telecommunication Systems
External Links
Snippet
Remote sensing technology is a vital component of disaster management, poised to revolutionize how we safeguard lives and property through enhanced prediction, mitigation, and recovery efforts. Disaster management hinges on continuous monitoring of various …
- 238000005516 engineering process 0 abstract description 77
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Alam et al. | Data fusion and IoT for smart ubiquitous environments: A survey | |
Munawar et al. | Disruptive technologies as a solution for disaster risk management: A review | |
Rathore et al. | IoT-based smart city development using big data analytical approach | |
Khajwal et al. | Post‐disaster damage classification based on deep multi‐view image fusion | |
Tian et al. | The development of key technologies in applications of vessels connected to the internet | |
Raihan | A comprehensive review of the recent advancement in integrating deep learning with geographic information systems | |
Albahri et al. | A systematic review of trustworthy artificial intelligence applications in natural disasters | |
Wei et al. | Survey of connected automated vehicle perception mode: from autonomy to interaction | |
Andersson et al. | Heterogeneous wireless sensor networks for flood prediction decision support systems | |
Kyrkou et al. | Machine learning for emergency management: A survey and future outlook | |
Ahmad | Smart remote sensing network for disaster management: an overview | |
Almalki et al. | Coupling multifunction drones with AI in the fight against the coronavirus pandemic | |
US20210048521A1 (en) | Systems, methods, apparatuses, and devices for facilitating performing of motion analysis in a field of interest | |
Gera et al. | Leveraging AI‐enabled 6G‐driven IoT for sustainable smart cities | |
Turukmane et al. | Multispectral image analysis for monitoring by IoT based wireless communication using secure locations protocol and classification by deep learning techniques | |
Gupta et al. | Smart remote sensing network for early warning of disaster risks | |
Cai et al. | Retracted: Smart city framework based on intelligent sensor network and visual surveillance | |
Solaiman et al. | Simultaneous Tracking and Recognizing Drone Targets with Millimeter-Wave Radar and Convolutional Neural Network | |
Srihith et al. | Future of Smart Cities: The Role of Machine Learning and Artificial Intelligence | |
Li et al. | Heterogeneous sensing for target tracking: architecture, techniques, applications and challenges | |
Gupta et al. | IoT, Enabling Technologies, and Sensor Node Deployment Pattern in WSN | |
Inam et al. | A comprehensive study on artificial intelligence algorithms to implement safety using communication technologies | |
Katambire et al. | Battery-Powered RSU Running Time Monitoring and Prediction Using ML Model Based on Received Signal Strength and Data Transmission Frequency in V2I Applications | |
Lin et al. | Special Issue Editorial: Advances in Computational Intelligence for Perception and Decision-Making for Autonomous Systems | |
Li et al. | A Review on Air-Ground Coordination in Mobile Edge Computing: Key Technologies, Applications and Future Directions |