E-Drone: Transforming the Energy Demand of Supply Chains Through Integrated UAV-to-land Logistics for 2030

NCT04990843 | Completed

• 3 other identifiers: RED 11731295372EP/V002619/1
• Study Type: observational
• Target: 24
• Locations: 1 country
• Sites: 4

Brief Summary

Vans are the fastest-growing category of licensed road vehicle in the UK with growing carbon dioxide (CO2) emissions. The proposed research into how Unmanned Aerial Vehicles (UAVs) and land logistics systems can be combined and managed will provide fundamental new understanding into the impacts of regulation and operating criteria on energy efficiency and costs. Medical logistics could be the first domain to utilise UAVs on a commercial scale, with preliminary analysis on pathology logistics within Southampton indicating that UAVs would significantly reduce CO2 emissions. With the National Health Service (NHS) spending an estimated £2.5 billion annually on pathology logistics and with patient numbers rising, there is a need to re-think how logistics costs could be reduced whilst improving bleed-to-diagnosis times for patients and energy demand. The research vision is to examine the energy reduction potential of logistics solutions involving UAVs operating alongside sustainable last-mile delivery solutions (cargo cycles and walking porters via micro-consolidation points). This involves understanding UAV operations in airspace shared with manned aircraft. The project focuses on a case study and trials based around NHS pathology sample transportation in the Solent and Dorset region. The key research objectives are to:

1. 1.Investigate the collective transport and energy impacts of current 'business-as-usual' NHS pathology logistics across the Solent region;
2. 2.Develop new simulation tools to quantify the energy consumption of UAVs and land logistics systems resulting from new types of traffic regulation for shared airspace and the operating requirements of UAVs;
3. 3.Evaluate the impact on air space and energy use of a large scale take-up of UAVs for medical logistics across the Solent region;
4. 4.Understand stakeholder concerns about UAVs;
5. 5.Understand the regulatory and governance needs associated with UAV interventions that will lead to energy benefits in logistics.

Conditions

Health Knowledge, Attitudes, Practice

Keywords

Un-crewed aerial vehicles; Integrated logistics; Healthcare; Energy demand; Social practices; Governance

Outcome Measures

Primary Outcomes (3)

• Questionnaire to a representative panel of the public

  To explore representations of UAVs

  1 - 33 months

• Questionnaire to a representative panel of the public

  To understand public concerns

  1 - 33 months

• Questionnaire to a representative panel of the public

  To determine how UAVs empower or constrain pathways to adoption

  1 - 33 months

Eligibility Criteria

• Age: 18 Years - 99 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

* Task 1.1 - health staff/managers dealing with dispatch or receipt of patient diagnostics, bloods or pharmacy products at hospitals and GP surgeries, and transport staff.. * Task 1.2 qualitative - key stakeholder groups involved in the project including, NHS staff, will be via the project teams' commercial partners, and the general public. * Task 1.2 quantitative - a representative sample of the UK population. * Task 1.3 - logistics staff and health staff/managers dealing with dispatch or receipt of patient diagnostics, bloods or pharmacy products at hospitals and GP surgeries. * Task 5.1 - key stakeholder groups involved in the project logistics providers, and a wider sample of the 144 organisations that responded to the Government consultation on the Future of Drones (January 2019). * Tasks 5.2 - Two sub-samples from task 5.1. * Task 6.2 - key stakeholders and members of the general public.

You may qualify if:

• Work Package 1
• Task 1.1: key informants in appropriate job roles, with attention purposefully paid to gender and age balance of participants.
• Task 1.2: Interviews - a purposeful recruitment strategy will seek participants with a range of socio-demographic characteristics. Questionnaire - Prolific (or a similar commercial company) will distribute the questionnaire (n\~1000) to achieve a representative sample of the UK population.
• Task 1.3: key informants in appropriate job roles, with attention purposefully paid to gender and age balance of participants.
• Work Package 5
• Stakeholders with an interest in UAV use with a purposeful selection of participants with a range of socio-demographic characteristics.
• Work Package 6 • Anyone interacting with the serious game in dissemination events.

Sponsors & Collaborators

• Bournemouth University: lead
• University of Southampton: collaborator
• University College, London: collaborator
• University of Leeds: collaborator

Study Sites (4)

Dorset County Hospital NHS Foundation Trust

Dorchester, Dorset, DT1 2JY, United Kingdom

Location

University Hospitals Dorset NHS Foundation Trust

Poole, Dorset, BH15 2JB, United Kingdom

Location

Portsmouth Hospitals University National Health Service Trust

Portsmouth, Hampshire, PO6 3LY, United Kingdom

Location

University Hospital Southampton NHS Foundation Trust

Southampton, Hampshire, SO16 6YD, United Kingdom

Location

MeSH Terms

Conditions

Behavior

Study Officials

• Janet Dickinson, Professor

  Professor in Tourism

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 15, 2021
• First Posted: August 5, 2021
• Study Start: January 1, 2021
• Primary Completion: December 31, 2023
• Study Completion: December 31, 2023
• Last Updated: January 11, 2024

Record last verified: 2024-01

Locations

GB (4)