Drone Assisted Robust Emergency Service Management for Elderly Chronic Disease

Area of Science:

• Gerontology
• Health Informatics
• Robotics

Background:

• Effective chronic disease management for the elderly is crucial but challenged by complex social networks and diverse service needs.
• Real-time, robust emergency services for elderly chronic disease patients are difficult to achieve with current systems.

Purpose of the Study:

• To design a novel drone-assisted robust emergency service system for elderly chronic disease management.
• To optimize drone deployment for minimizing total time cost while meeting service demands and energy constraints.

Main Methods:

• Formulated the Drone assisted Management (DM) problem to minimize drone time cost.
• Developed the Drone assisted Management (DM) problem and the Drone assisted Management (DM) algorithm (DRS) to address service guarantees and energy constraints.
• Introduced the Charging driven Drone assisted Management (CDM) problem and the Charging driven Drone assisted Management (CDM) algorithm (CDRS) for enhanced robustness and real-time service.

Main Results:

• The DRS algorithm decreased total time cost by 37.61%.
• The CDRS algorithm significantly improved the Quality of Experience (QoE) by 112.80%.
• Both algorithms demonstrated effectiveness through theoretical analysis and numerical simulations.

Conclusions:

• The developed drone-assisted system provides a robust and real-time solution for elderly chronic disease emergency services.
• The DRS and CDRS algorithms offer significant improvements in efficiency and service quality for elderly healthcare.
• This technology has the potential to revolutionize emergency response for chronic disease management in aging populations.