***
*The 3rd Workshop on Artificial Intelligence for Networked Drone and Sensor
Applications (DroneSense-AI 2026), to be held in conjunction with IEEE
WoWMoM 2026.*
*Theme: Advancing AI for the Low-Altitude Economy and Satellite-Augmented
Drone Networks*
*Website: **https://sites.google.com/view/dronesense-ai2026/home-2026
<https://sites.google.com/view/dronesense-ai2026/home-2026>*
The Workshop on Artificial Intelligence for Networked Drone and Sensor
Applications (DroneSense-AI) aims to bring together researchers,
practitioners, and industry experts to explore the integration of machine
learning (ML) and Artificial Intelligence (AI) with networked drones and
intelligent sensor systems. This convergence continues to reshape sectors
such as agriculture, environmental monitoring, disaster response, critical
infrastructure, and public safety. Within the context of the emerging
*Low-Altitude
Economy (LAE),* the demand for AI driven coordination, perception, and
decision making is growing rapidly.
ML/AI enabled drone and sensor systems can process large volumes of
heterogeneous, real-time data to enable autonomous behavior, dynamic
coordination, and mission aware optimization. To support these operations
at scale, particularly for missions operating Beyond Visual Line of Sight
(BVLOS), the integration of *Satellite augmented connectivity* is emerging
as a critical infrastructure layer alongside terrestrial networks.
However, challenges such as processing latency, data integration,
communication constraints, energy efficiency, and the lack of standardized
architectures remain major barriers to widespread adoption. Promising
avenues for overcoming these limitations are emerging, particularly in the
form of quantum processing and secure communication. This workshop will
address the technical challenges, emerging solutions, and application
scenarios of ML/AI integration in distributed drone and sensor networks. It
will provide a timely platform to present novel algorithms, deployment
strategies, and scalability insights with an emphasis on real world impact
and cross-disciplinary innovation.
The timeliness of this workshop is underscored by growing academic and
industrial investment in ML driven autonomous systems, along with the rapid
expansion of drone-enabled services. As such, this workshop provides a
timely forum for researchers, developers, and practitioners to exchange
ideas, share methodologies, and identify future directions in ML enhanced
Internet of Drone (IoD) and Internet of Things (IoT) systems.
*Topics of Interest*
We invite original contributions on the following topics :
*ML & AI Integration*
- Architectures for ML deployment in UAV/sensor networks
- Edge and distributed learning for drones and IoT
- Communication-efficient AI models for UAV swarms
- AI-based anomaly detection and pattern recognition
*Drone Operations & Autonomy*
- UAV navigation and real-time trajectory optimisation
- Multi-agent coordination and swarm intelligence
- AI for dynamic flight control and formation
- Safety-aware autonomous drone systems
*Environmental & Agricultural Applications*
- AI for crop health monitoring and yield prediction
- Biodiversity tracking and habitat surveillance
- UAV-enabled smart farming and remote sensing
- Forest fire and disaster detection using AI
*Infrastructure, Industry & Logistics*
- AI-powered infrastructure inspection and asset monitoring
- Predictive maintenance using UAV-collected data
- Autonomous delivery and drone-based logistics
- Industry 4.0 integration with UAV and IoT platforms
*Security, Surveillance & Public Safety*
- ML for real-time object/person detection
- AI-based threat assessment and crowd monitoring
- Privacy-preserving AI in surveillance drones
- UAVs for law enforcement and emergency response
*Healthcare & Emergency Services*
- UAV-based delivery of medical supplies
- Real-time patient monitoring and telemedicine via drones
- AI for emergency triage and disaster relief coordination
*Connectivity & Networks*
- UAV-enabled IoT and wireless data collection
- AI-optimised drone-assisted cellular network coverage
- Communication protocols for dense UAV-sensor networks
- *Satellite-Augmented Drone Systems:*
- AI for seamless handovers between terrestrial (5G/6G) and LEO
satellite links
- Satellite-backhauled edge computing for remote drone operations
- Distributed AI for space-air-ground integrated sensing
- Resilient navigation and positioning in GNSS-denied environments
*Emerging Paradigms*
- Quantum-enhanced communication and processing for UAVs
- Quantum and mmWave sensing
- Ethical and regulatory considerations in AI-based drone systems
- Simulation environments and benchmarking for drone-AI research
*Workshop Chairs: *
- Associate Professor Jahan Hassan (Central Queensland University,
Australia)
- Associate Professor Biplob Ray (Central Queensland University,
Australia)
- Associate Professor Jaime Galán-Jiménez (University of Extremadura,
Spain)
- Dr Shuvashis Dey (North Dakota State University, USA)
📅* Important Dates*
- Paper submission deadline: 22 March, 2026
- Paper acceptance notification: 12 April,2026
- Camera-ready version due: 26 April, 2026
- Workshop Date: 16 - 19, June 2026
*Submission & Contact*
- Submission Link via EDAS: https://edas.info/newPaper.php?c=35067
- Workshop Website:
*https://sites.google.com/view/dronesense-ai2026/home-2026
<https://sites.google.com/view/dronesense-ai2026/home-2026>*
- Contact Email: *j.hassan@cqu.edu.au <j.hassan@cqu.edu.au>*;
b.ray@cqu.edu.au
*****Journal Special Issue Invitation*****
Selected authors will be invited to submit an extended version of their
workshop papers to the Elsevier Ad Hoc Networks (Q1) Special Issue titled
"Intelligent and Resilient Networking for the Low-Altitude Economy: From
Autonomous Systems to Scalable Services." *Please note that submissions
must represent a substantial extension of the original workshop paper. This
may include new theoretical analysis, enhanced or redesigned
algorithms/models, and significantly expanded experimental validation
(e.g., new datasets, additional baselines, new evaluation metrics, and
deeper performance analysis). All submissions will undergo the journal's
standard peer-review process.*
Special Issue website: https://tinyurl.com/89t4abwb
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