Dr-UBER: Drone Network for Medical Emergency Delivery in Essex
- Funded by UK Research and Innovation (UKRI)
- Total publications:0 publications
Grant number: 10107757
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Key facts
Disease
Disease XStart & end year
20242025Known Financial Commitments (USD)
$126,252.22Funder
UK Research and Innovation (UKRI)Research Location
United KingdomLead Research Institution
AIRBORNE ROBOTICS LIMITEDResearch Priority Alignment
N/A
Research Category
Health Systems ResearchResearch Subcategory
Health service deliverySpecial Interest Tags
InnovationStudy Type
Non-ClinicalClinical Trial Details
N/ABroad Policy Alignment
PendingAge Group
Not ApplicableVulnerable Population
Not applicableOccupations of Interest
Not applicable
Abstract
Dr-UBER envisions establishing an urban multi-drone network for emergency medical and healthcare services, employing a "ride-hailing" concept to connect medical institutions, including hospitals, pharmacies, doctors/GPs, and medical laboratories. This innovative approach aims to facilitate the swift and secure delivery of emergency healthcare/medical services, such as defibrillators (AEDs) or blood, addressing availability and distribution challenges and, more importantly, increasing the survival rate of individuals experiencing out-of-hospital cardiac arrest (OHCA). In pursuit of this goal, Airborne Robotics (AIRBORNE) and Anglia Ruskin University (ARU), as the subcontractor, propose a feasibility study to develop a multi-drone network providing "fly and deliver" services in Chelmsford, Essex. Chelmsford's strategic selection is based on its proximity to London and the challenges posed by congested roadways like the A12 and M11\. Identifying drone no-fly zones in and around the area serves as both a challenge to address and a practical context for the use-case study. Beyond addressing service demands, the project will carefully assess and integrate regulations in aviation and medicine, ethical considerations, and the safe and secure operation of drones into the network architecture. The technical assessment will encompass factors influencing drone performance, including navigation systems, communication (speed, latency, data security), sensors, battery health, environmental conditions (weather), airspace access, detect and avoid (DAA) collision, and remote piloting and operation. Considering these intricate factors, a scalable, dynamic geofencing module and an Artificial Intelligence (AI)-driven "routing and scheduling" algorithm will be developed and integrated into the Dr-UBER urban multi-drone network. This integration presents an opportunity for nationwide implementation of Dr-UBER. The study will evaluate the viability of the multi-drone network for operationalising emergency healthcare/medical services, thereby contributing to the support of the NHS. The data derived from the project will guide AIRBORNE in formulating a strategy for commercialisation, including seeking a particular CAA-Operating Safety Case permission. Given the surge in online prescriptions and the heightened demand for same-day delivery, exacerbated by the COVID-19 pandemic, there is a belief that Dr-UBER can significantly enhance healthcare logistics and bolster resilience within its supply chain.