Prevention of Epidemics Using IoT-based Contact Tracing

Early Detection and Prevention of Epidemics Using IoT-based Contact Tracing

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The world has been facing multiple epidemic events in the past few years. All these are majorly caused due to rapid urbanization and deforestation.

Epidemics in the past decade
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A majority of these epidemic viruses are transferred from animals to humans and then are spread through human-to-human contact. The rapid spread of misinformation during the epidemic further adds fuel to the fire. These infodemics boost up the spread of these viruses. 


Rapid globalization is the one major troubling aspect of the epidemics occurring in the 21st century. The epidemics in the 21st century are spreading faster and further than ever. Outbreaks that were previously localized can now become global very rapidly – just as fast as an intercontinental aircraft can fly. So, an individual flying from one side of the world can introduce a new disease into another side, within hours, and before even showing symptoms. And in this way, far from its origins, the microbe finds a new home and eventually manages to mutate and spread. 


In 2015, it took just one traveler returning home to the Republic of Korea to bring MERS back with him. The consequences caused a major Korean outbreak with 186 cases, 36 deaths, and outbreak-related losses of approximately $8 Billion, all in a time span of two months. The recent COVID-19 pandemic started in a similar manner and it has brought the whole world to its knees.


Tracing and Detecting Outbreaks Before They Turn into Epidemics

Given the effects of globalization, the intense mobility of human populations, and the relentless

urbanization, it is likely that the next emerging virus will also spread even faster. It is impossible to predict the nature of this virus or its source, or where it will start spreading. Also, considering that most of the deadly virus infections have very common symptoms like fatigue, fever, sore throat, runny nose, etc., it is nearly impossible to detect and curb the spread right at the source.

major epidemics and their common symptoms
Major epidemics and their common symptoms


No matter how prepared we are for the next epidemic, there is no way to completely prevent it for these reasons:

  • Initial delay in recognizing it
  • Once the virus is recognized, tracing the source and isolating it from the rest of the world is like finding a needle in a haystack
  • Once the spread becomes public knowledge, there will be a subsequent infodemic, aided and abetted by media coverage, causing the virus to spread even further

Epidemics have 4 phases.

Epidemic progression phases
Epidemic progression phases


Ideally, the pandemic can be prevented if the virus is detected and isolated at the emergence stage. But like we discussed above, it is nearly impossible unless we are anticipating the emergence of the virus.

When localized transmissions start, if the first responders get into action right away and contain the virus, we can still prevent a major worldwide epidemic. But for first responders to be able to curb the spread of the epidemic, they require the capabilities to gather data to determine details  like:

  • Potential victim count
  • Type of emergency
  • Scale and severity of the outbreak
  • Tracing the source and the spread pattern
  • Identification and tracking of early symptoms in the vicinity
  • Personal protection checklist

The Existing Manual Contact Tracing and Detection System

Epidemic outbreaks often originate in rural and remote areas. Outbreaks go undetected in poor communities around the world where there is limited access to medical facilities. It only gets noticed when the outbreak reaches cities. By then, the time to curb and contain the outbreak right at its source is long gone. This has major implications when an infectious threat occurs. For example, the Ebola outbreak in West Africa remained undiagnosed for more than two months. This time lag allowed the virus to freely spread undetected, and reach capital cities where it grew into a large epidemic. The initial response and detection time plays a major role in preventing local outbreaks from turning into global epidemics.

The most effective way of slowing down an epidemic is contact tracing, which should start at the stage of localized transmission. The present contact tracing system is manual. This works by tracking down potentially infected individuals and preventing them from further spreading the virus. Contact tracers interview every known infected person and then follow up with all of their recent contacts and isolate them. This requires the infected person to recollect all the people she/he has come into contact with and the places they have visited in the past couple of weeks. This is an extremely ineffective method. 

Think about it – do you remember every hotdog vendor you stopped by, or who stood next to you in the queue at the bank, or who sat next to you on the bus? Also, a lot of infected people are not willing to participate in the contact tracing interviews as they feel it violates their privacy. Contact tracing is a time-sensitive task and the inefficiency of the system further complicates matters. Additionally, all the manual tracing systems are disconnected from each other. So there is no way to integrate all the data and see the greater picture right away.

The present tracing and detection systems have 3 major limitations

  • More time is spent in collecting information
  • Loss of information due to human factors
  • Emergency Response Framework (ERF) lacks time for outlining action items or control measures
Existing contact tracing system
Existing contact tracing system


The existing manual tracing system comes into action after a large number of infected people have already traveled and spread the outbreak at multiple places. As the outbreak progresses and branches towards different regions, it becomes difficult to trace it back to the point of origin and detect modes of transmission. While healthcare systems struggle to figure out ways of containment, we already have a major epidemic at hand.

Contact Tracing System using Computer Vision and IoT

Considering the limitations of the present manual tracing system, it is obvious that we require an automated system that is efficient. The modern automated contact tracing system can be built by using technologies like Computer Vision and IoT.

Contact tracing system with IoT and Computer Vision
Contact tracing system with IoT and Computer Vision


The system will be capable of accessing databases of patients across every hospital and generate a list of people a particular patient has come in contact with, before getting isolated. The system will consist of a Face Detection algorithm, Contact Audit System, a feature to allow multiple support systems to capture symptoms/adherence (thermal scanning, cough detection, facemask detection, future AI). The images of the hospitalized patients will be the initial input for the system and then the contact tracing will happen across all the locations the patients have visited. It will generate a report with details of people exposed to the virus and also determine the level of exposure. Based on these details, healthcare workers can locate and isolate people before the contamination spreads.

The Computer Vision and IoT based contact tracing system will consist of 3 main components

The Contact Audit System

The Contact Audit System
The Contact Audit System


This system will connect to all the surveillance cameras in public places and the computer vision tool will calibrate them to transform perspective view to birds-eye view. With this view, contact tracing will be easier and the system can detect people using Faster R-CNN architecture. Based on the view angle, the system can also be calibrated to measure the distance between different points, and so it can offer accurate contact tracing results using proximity. In the case of high-density spaces, LiDAR (Light Detection and Ranging) can be used.

The Face Detection System

The Face Detection System
The Face Detection System


Once the contact audit system has spotted all the individuals who may have been exposed to the virus, the face recognition system can help identify those individuals.

The system can use dlib or OpenCV to capture the required images. The captured images will further be sent to the Deep Neural Network. The deep neural network will embed the face on a 128-dimensional unit hypersphere with an accuracy of 92.92 in LFW. The results will provide a reliable list of people at high risk due to the virus.

Multiple Support Systems to capture Symptoms / Adherence

Multiple Support Systems to capture Symptoms / Adherence
Multiple Support Systems to capture Symptoms / Adherence


During an outbreak, there are always chances that people who are infected with the virus but are asymptomatic. These asymptomatic people can further infect other people. As there is no contact tracing trail possible in such scenarios, people infected with the virus are roaming around unaware that they are sick. The support system will take care of all these scenarios by scanning individuals for symptoms. Radiometric thermal measurement can be done using thermal scanners. Whenever a higher temperature is detected, the thermal scanner will relay the data to the face detection system where the tagged face will be recognized. The support system can also help with detecting adherence to social distancing rules. Face-mask detection for all individuals can help the system rate potential victims based on adherence.

Automated contact tracing system
Automated contact tracing system

The Futuristic Contact Tracing System

This concept of the Contact Tracing system, if implemented, would prove to be a game-changer in our battle against future epidemics and pandemics. An efficient contact tracing system can help prevent public hotspots for virus spreading. Healthcare workers can contain the virus before it turns into a global pandemic.