• Users Online: 191
  • Print this page
  • Email this page

Table of Contents
Year : 2020  |  Volume : 17  |  Issue : 5  |  Page : 58-61

Automated COVID-19 emergency response using modern technologies

1 School of Engineering Sciences and Technology, Jamia Hamdard, India
2 Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi, India

Date of Submission07-Jul-2020
Date of Acceptance25-Jul-2020
Date of Web Publication05-Aug-2020

Correspondence Address:
Mohd Javaid
Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/am.am_68_20

Rights and Permissions

Almost all countries are struggling with a pandemic created by infection of the severe acute respiratory syndrome coronavirus-2 virus. Health professionals are overstretched and are estimating to treat millions of peoples infected by this virus. However, we see the gainful employment of new technologies to provide fewer human interaction benefits to prevent the transmission of this virus. Here, in this paper, the capabilities of new technologies such as unmanned aerial vehicles, data analysis, three-dimensional (3D) printing, machine learning, and artificial intelligence are used to develop a model to the limit of their autonomous functionalities. We have proposed an automated COVID-19 pandemic emergency response system using the above modern technologies. These technologies are used efficiently to supply essential items in the required location and minimize the need for transportation. Advanced digital technologies are used to observe the crowd in different cities. It can identify people who are not wearing masks in public places. Further, 3D printing technology is used to manufacture personal protective equipment for COVID-19, and drones are used to deliver these items in the required places. The integrated deployment of new technologies can help us to fight this virus in a better way. This model can help through intelligent population screening, improved medical help, timely notification, and suggestions about infection control. It uses an innovative platform supported through different software and machine learning techniques. Furthermore, doctors, analysts, governments, and researcher can take its advantage to analyze the level of infection by the virus.

Keywords: Artificial intelligence: Automatic emergency response system, COVID-19, pandemic, three-dimensional printing, unmanned aerial vehicles

How to cite this article:
Khan IH, Javaid M. Automated COVID-19 emergency response using modern technologies. Apollo Med 2020;17, Suppl S1:58-61

How to cite this URL:
Khan IH, Javaid M. Automated COVID-19 emergency response using modern technologies. Apollo Med [serial online] 2020 [cited 2021 Oct 20];17, Suppl S1:58-61. Available from: https://www.apollomedicine.org/text.asp?2020/17/5/58/291470

  Introduction Top

There is a desperate shortage of daily usage goods, which has put significant stress on the people and governments. During this COVID-19 crisis, there is a massive load on our health-care system. The lockdown in several countries such as India has affected production, manufacturing, transportation, and logistics. Supply chains of almost all products and services are severally affected. The educational field is directly affected due to the closure of educational institutions. It affects the film and event management industry by which all facilities are closed. All shows of the ongoing movies are postponed or canceled.[1],[2]

University of South Australia researchers partnered with Draganfly Inc., A Canadian Company, for developing a drone that can remotely help to detect the patient of the COVID-19 virus. It helps to monitor offices, crowds, airports, long-term care homes, nursing, cruise ships, and other group scenarios. Drone-based video is also used to detect the heart rate of a human. In Ireland, this technology is used to deliver various medicines, insulin, and other essential items in the right place. The United States has implemented drone technology for both rural and metropolitan areas to fulfill various challenges of COVID-19. This technology is used to deliver medical supplies of COVID-19 test kits, medication delivery in rural areas, and remote monitoring of patient symptoms. This technology is successfully maximizing the safety of health-care professionals.[3],[4] Research is required to fulfill the need for essential items and proper monitoring of the health-care system. Hence, technologies such as unmanned aerial vehicles (UAVs), data analysis, three-dimensional (3D) printing, machine learning, and artificial intelligence (AI) are introduced in this paper to provide an automatic pandemic response system.

  the Crisis Arose during Covid-19 Pandemic Top

The retailing of various consumable items has got impacted, and at many places, shops dealing with the nonemergency items have been closed down. There is a shortage of medical equipment; large corporations are asked to make masks, ventilators, kits, and other necessary types of equipment to help prevent this disease. However, they are facing a huge logistic issue.

Tour and travel industry is one of the worst-hit sectors, here most of the international and domestic traveling is suspended, and tourists have canceled their programs and other significant events worldwide. There is shutting down of many, even the shooting of television programs in several countries. Many international sporting events are postponed.[5],[6]

The governance structures are being questioned. Peoples are angry about the situation; even on those who are governing them, there is massive frustration. They are questioning the massive expenditure on armament and research support to the armament industry; instead, if these resources would have been used for public health, no such type of pandemic would have occurred. Sometimes, this anger is directed toward the people who are directly or indirectly responsible for spreading this virus. Further, we see that people's anger erupts on those who are managing the disaster. Peoples are willing not to do anything and want to stay safe from the virus. The public must avoid public transport, crowed, and closed space. Unfortunately, social media are creating undue fear and rumors, and it is de-motivating people. There is also cancelation and postponement of social activities such as marriage, weddings, vacations, and other recreational activities.[7],[8]

During this pandemic, delivery/logistics is a huge issue and a need. Hence, we introduce a model of automated COVID-19 Pandemic Emergency Response System using different technologies. Here, the problem is solved by introducing a Command Center (CC) which interacts, interprets the figures using data analyses and factors it using machine learning, and predicts needs and preready delivery and launching systems using AI.

The major steps used by different technologies to provide an automated COVID-19 Pandemic Emergency Response system are discussed in the following steps:

Step I

CC gets the requirements from multiple sources. Here, using and confirming the order segmentation is required like:

  • Need for personal protective equipment (PPE)
  • Need for medicines and kits

    1. Aerial sample collection
    2. Delivery of medicinal equipment.

  • Need for food items
  • Need for geographical surveillance for crowd control
  • The need for help and rescue systems or guidance system.

Step II

The Command system analyzes the request and requirements while giving each and every task a priority statusp(x). According to thep(x), it sorts the duty and auto equip-mentation of UAV initiates. The manufacturing and production plants also get informed.

Step III

If there is a need for PPE at a hospital or an emergency makeshift treatment center, then the CC sends a request to multiple 3D printing facilities and immediately informs the automated centers about thep(x), order details, criteria, and time. The centers send the CC an Estimate time arrival (ETA) for the prints; accordingly, the UAVs are launched to the facilities. The number of UAVs launch to a destination is determined by the factor of weight (W), size (X, Y, Z), and distance (displacement D). When ETA is equal to the drone's time to the travel to a specific the facilities, the UAV automatically initiates the launch and starts the mission. It lands to the specific area, collects the box under its limits while scanning a code for its authenticity, and relaunches again for the CC. All the information is transferred in real time to the CC and where a system analyzes and predicts the arrival and schedules the delivery of collected items to its desired location after a computerized inspection using machine learning and AI trained over previous data. Then, the UAV returns to CC, a scheduled automated system check is performed, and service is also performed.

Whenever a CC receives a request for medicines and kits, it first analyzes and requests the health and medicinal manufacturing centers about the availability of the Articles (A); if yes, then Quantity (Q), W, T, and S are determined. If no, it precedes to final, a manufacturing unit that matches the requirement. They are collected by a UAV, which returns to the CC if the battery is not sufficient or any other technical difficulties are there, correct them, and fly them to the destination else the UAV launches toward the final delivery point immediately and then return to CC for inspection. If there is a requirement of a sample check, specialized UAVs are launched with bigger batteries and higher endurance to the medical checkup facilities, they automatically collect and delivery the samples with the help of a CC, keeping it updated for every single point. Similarly, the food is delivered to the location using the help of CC and collected and delivered to the doorstep of people.

Step IV

When there is potential feedback from the system to analyze a situation, it launches UAVs packed with its controllers and scans the area and marks them red, blue, and green according to the severity they have been allocated to. The controllers are dropped with the authorities for manual control and carry extra sets of batteries and other modules. After the inspection, all the data go to the CC through MAVLink. Furthermore, display guidance is in the authority's app of the tablet and laptops.

Step V

The drone can act as a guidance system in rescue mission any number of people; it can be connected to a loudspeaker or display to caution and guide people to a safe or authoritative sight. In this process, all activities are controlled by the automated CC, as shown in [Figure 1].
Figure 1: The automotive Command center controls activities

Click here to view

Updating to CC at every stage reduces the chances of mishaps, crashes, and failures, leading to more natural recovery.

The central concept behind this scheduler is the less to nonhuman interaction with the machine to the system. The data analyzed is fed to the controller, which in turn decides logistics and problem-solving with the help of heavy trained AI in the aspects of failures, services, DOM, modules, priority, risk, flight, object tracking, scheduling, identification, patterns, flying conditions, delivery status, success mission, and other major key roles. The basic outlines of service using different technologies are shown in [Figure 2].
Figure 2: Basic outline of a service using these technologies

Click here to view

A CC is used to control all activities of needs, production, services, and overriding. AI is also used, which can provide early diagnosis and testing of the patient to identify the suspect of COVID-19 patient at an early stage and to evaluate the infected patient at an individual level. It is efficient for reasoning, planning, learning, and knowledge representation.[9],[10],[11] In the future, AI could combine robotic technology to achieve proper treatment and COVID-19 outcomes. This technology quickly adopts changes in various surgical procedures and can be applied to any infection problem in the world, war, and barriers where human interaction is not safe.

This will help reduce the country's economic stress and even lessen the stress on human delivery chains. Even putting aside concerns about public health, it appears that there is a significant economic trade-off whether or not we impose social distancing – the economic costs of strong social distancing measures imposed for an entire 12–18 months on the one hand or the economic costs of an enormous cumulative burden of lost work time 3 (and life) due to the disease. Which option would have more severe economic consequences is hard to determine.[12]

  Conclusion Top

UAVs, data analysis, 3D printing, machine learning, and AI are innovative technologies which can fulfill various challenges faced by COVID-19 crisis with their proper integration. CC gets the requirement of essential items and various controlling activities. Some items can also be printed using proper 3D printing technologies, and drones are applied to deliver these essential items in the required place. AI is used for an automatic checkup of the performance of the required services. These technologies are helpful for the research and development to provide proper treatment and precautions regarding COVID-19 virus. These quickly collect the data to make a real-time health map for several people affected by this virus.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Grasselli G, Pesenti A, Cecconi M. Critical care utilisation for the COVID-19 outbreak in Lombardy, Italy: Early experience and forecast during an emergency response. JAMA2020;323:1545-6.  Back to cited text no. 1
Javaid M, Haleem A, Vaishya R, Bahl S, Suman R, Vaish A. Industry 4.0 technologies and their applications in fighting COVID-19 pandemic. Diabetes Metab Syndr 2020;14:419-22.  Back to cited text no. 2
Meszaros L. Drone Technology: A New Ally in the Fight against COVID-19. MD Linx. Available from: https://www.mdlinx.com/internal-medicine/article/6767. [Last accessed on 2020 Apr 08].  Back to cited text no. 3
Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W, et al. Correlation of chest CT and RT-PCR testing for coronavirus disease 2019 (COVID-19) in China: A report of 1014 cases. Radiology 2020;296:E32-40.  Back to cited text no. 4
Epidemiology Working Group for NCIP Epidemic Response, Chinese Center for Disease Control and Prevention. The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China. Zhonghua Liu Xing Bing Xue Za Zhi 2020;41:145-51.  Back to cited text no. 5
Luo H, Tang QL, Shang YX, Liang SB, Yang M, Robinson N, et al. Can Chinese medicine be used for prevention of corona virus disease 2019 (COVID-19)? A review of historical classics, research evidence and current prevention Programs. Chin J Integr Med 2020;26:243-50.  Back to cited text no. 6
Bobdey S, Ray S. Going viral–COVID-19 impact assessment: A perspective beyond clinical practice. J Mar Med Soc 2020;22:9.  Back to cited text no. 7
  [Full text]  
Cinelli M, Quattrociocchi W, Galeazzi A, Valensise CM, Brugnoli E, Schmidt AL, et al. The COVID-19 Social Media Infodemic. arXiv preprint arXiv: 2003.05004. 2020. Available from: https://arxiv.org/abs/2003.05004. [Last accessed on 2020 Jul 25].  Back to cited text no. 8
Spina S, Marrazzo F, Migliari M, Stucchi R, Sforza A, Fumagalli R. The response of Milan's emergency medical system to the COVID-19 outbreak in Italy. Lancet 2020;395:e49-50.  Back to cited text no. 9
Rao AS, Vazquez JA. Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone-based survey in the populations when cities/towns are under quarantine. Infect Control Hosp Epidemiol 2020;3:1-8.  Back to cited text no. 10
He F, Deng Y, Li W. Coronavirus Disease 2019 (COVID-19): What we know? J Med Virol 2020;92:719-25.  Back to cited text no. 11
Atkeson A. What Will Be the Economic Impact of COVID-19 in the US? Rough Estimates of Disease Scenarios. The National Bureau of Economic Research, NBER Working Paper No. 26867. 2020; [doi: 10.3386/w26867].  Back to cited text no. 12


  [Figure 1], [Figure 2]

This article has been cited by
1 Exploring the Potentials of Automation in Logistics and Supply Chain Management: Paving the Way for Autonomous Supply Chains
Benjamin Nitsche
Logistics. 2021; 5(3): 51
[Pubmed] | [DOI]
2 The role of 3D printing during COVID-19 pandemic: a review
Guilherme Arthur Longhitano,Guilherme Bitencourt Nunes,Geovany Candido,Jorge Vicente Lopes da Silva
Progress in Additive Manufacturing. 2020;
[Pubmed] | [DOI]


    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

  In this article
the Crisis Arose...
Article Figures

 Article Access Statistics
    PDF Downloaded136    
    Comments [Add]    
    Cited by others 2    

Recommend this journal