Needs Assessment

Objective

We aim to optimize triage and medical efforts in mass-casualty incidents (MCIs) by leveraging unmanned vehicles to gather and evaluate injuries. The scope of this project includes:

• Optimal area searching algorithms for drones

• Identification of casualties and their injuries

• Organizing salient disaster data to improve triage and medical response

• Enabling communication between victims and medical teams using speakers, microphones, and cameras

In order to:

• Increase accuracy of triage

• Improve real-time decision making

• Better our understanding of MCIs in the long term through data collection

Background

MCIs are disasters, either man-made or natural, in which local management agencies and the healthcare system are overwhelmed. The impact of these incidents are severe, where an estimated 10 to 20 thousand people die annually from natural disasters alone [1]. Proper triage efforts are crucial, where an analysis of previous disasters found that 25-50% of injuries and deaths are preventable given proper treatment [2]. 

Current MCI responses face the following problems:

• Overwhelming environment: MCIs are often chaotic, sometimes containing collapsed structures and stretching over large regions. Searching for victims in this environment with humans on foot is therefore a daunting task.

• Mistriage: Even if a person is discovered, our current triage systems are often inflexible and insufficient to address specific situations. The Emergency Severity Index used in the United States for triage was estimated to mistriage 1/3 of patients [3]. Real-time data collection of MCIs are critical to improve our response triage protocols.

• Constrained resources: Limited availability of medical supplies and equipment, coupled with shortages in healthcare personnel, often hampers swift and adequate assistance. Communication breakdowns further exacerbate the situation, impeding coordination among response agencies. Moreover, financial constraints strain local budgets, hindering preparedness and response initiatives.

• Worker safety: Based on the type of MCI healthcare workers may be put at risk. Rescure works at Fukushima where reqired to receive cancer screening based on exposer. 9/11 had an estimated 90,000 rescue workers of which some suffered both physical and mental health effects [4]. It is important to reduce time in field required for effective triage

Various regions stand to benefit significantly from the deployment of unmanned vehicles, including:

• Warzones

• Natural Disasters

• Terrorist Attacks

• Industrial Accidents

• Transportation Accidents

Methodology

The unmanned aerial and ground vehicles will effectively search disaster areas and identify injuries. Next, they will classify the casualties' injuries based on severity. Data collected on injuries will then be reported back to emergency response teams. Communication between responders and victims will also be enabled through microphones and speakers in the devices.

Expected Results

Our expected result for this project is to provide optimal care to patients and victims.  By improving the capacity and accuracy of triage in both the battlefield and civilian settings, we can rapidly identify causalities with critical injuries and deliver treatments as quickly as possible.

Costs

The average high-end drone costs $3000 [5] and the cost of an average military UGV is around $3700[6].

Unlike high altitude surveying, using UVTs for triage would require a greater quantity of drones to cover the same area, since they would need to sweep areas at a lower altitude to find humans. 

The cost of each MCI will vary based on the number of drones needed, and scale alongside disaster area and terrain complexity. 

For example, assuming the requirement of 100 drones, the initial costs would be $37,000.

Further analysis is needed, but based on this preliminary information, we estimate that the ability to recurringly use drones should spread the initial cost over multiple disasters.

Other costs to consider include:

• UVT maintenance, storage, and energy

• Video and audio data storage for UVTs

• Software development