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SecureTrack- A contact tracing IoT platform for monitoring infectious diseases

Cryptography and Security · Submitted 19 Jul 2023

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim We develop the architecture of our platform, including both the frontend and backend components, and demonstrate its effectiveness in identifying potential COVID-19 exposures (as a test case) through a proof-of-concept implementation.

how it is stated · asserted 1.00 read the record →

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arXiv ID2307.10311 (version 1)
Pith IDZ2RLND42, Pith's permanent record of this paper and its review
CitationArnab Purkayastha, Shobhit Aggarwal. "SecureTrack- A contact tracing IoT platform for monitoring infectious diseases." arXiv:2307.10311 (2023). https://pith.science/paper/Z2RLND42
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 7,488 input tokens.

What the abstract itself states, as probabilities: claims first 0.12 · states limitation 0.16 · human participants 0.30 · controlled comparison 0.04 · randomized assignment 0.01 · states quantitative result 0.04 · compares with prior results 0.19 · mentions code or data availability 0.04.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

The COVID-19 pandemic has highlighted the need for innovative solutions to monitor and control the spread of infectious diseases. With the potential for future pandemics and the risk of outbreaks particularly in academic institutions, there is a pressing need for effective approaches to monitor and manage such diseases. Contact tracing using Global Positioning Systems (GPS) has been found to be the most prevalent method to detect and tackle the extent of outbreaks during the pandemic. However, these services suffer from the inherent problems of infringement of data privacy that creates hindrance in adoption of the technology. Non-cellular wireless technologies on the other hand are well-suited to provide secure contact tracing methods. Such approaches integrated with the Internet of Things (IoT) have a great potential to aid in the fight against any type of infectious diseases. In response, we present a unique approach that utilizes an IoT based generic framework to identify individuals who may have been exposed to the virus, using contact tracing methods, without compromising the privacy aspect. We develop the architecture of our platform, including both the frontend and backend components, and demonstrate its effectiveness in identifying potential COVID-19 exposures (as a test case) through a proof-of-concept implementation. We also implement and verify a prototype of the device. Our framework is easily deployable and can be scaled up as needed with the existing infrastructure.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 The COVID-19 pandemic has highlighted the need for innovative solutions to monitor and control the spread of infectious diseases. background 1.00 0.04 0.03 asserted 1.00
s1 With the potential for future pandemics and the risk of outbreaks particularly in academic institutions, there is a pressing need for effective approaches to monitor and manage such diseases. background 0.99 0.04 0.02 asserted 0.78
s2 Contact tracing using Global Positioning Systems (GPS) has been found to be the most prevalent method to detect and tackle the extent of outbreaks during the pandemic. background 1.00 0.07 0.03 asserted 1.00
s3 However, these services suffer from the inherent problems of infringement of data privacy that creates hindrance in adoption of the technology. background 0.84 0.07 0.03 asserted 1.00
s4 Non-cellular wireless technologies on the other hand are well-suited to provide secure contact tracing methods. background 0.96 0.09 0.07 asserted 0.92
s5 Such approaches integrated with the Internet of Things (IoT) have a great potential to aid in the fight against any type of infectious diseases. background 0.98 0.07 0.09 hedged possibility 0.82
s6 In response, we present a unique approach that utilizes an IoT based generic framework to identify individuals who may have been exposed to the virus, using contact tracing methods, without compromising the privacy aspect. contribution 1.00 0.92 0.45 asserted 0.95
s7 We develop the architecture of our platform, including both the frontend and backend components, and demonstrate its effectiveness in identifying potential COVID-19 exposures (as a test case) through a proof-of-concept implementation. contribution 0.93 0.97 0.21 asserted 1.00
s8 We also implement and verify a prototype of the device. contribution 0.80 0.96 0.05 asserted 1.00
s9 Our framework is easily deployable and can be scaled up as needed with the existing infrastructure. contribution 0.40 0.65 0.22 asserted 0.98

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from observation or experiment 0.88.

What was examined, and what was not

sources read
  • arXiv listing abstract v1
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

The COVID-19 pandemic has highlighted the need for innovative solutions to monitor and control the spread of infectious diseases. With the potential for future pandemics and the risk of outbreaks particularly in academic institutions, there is a pressing need for effective approaches to monitor and manage such diseases. Contact tracing using Global Positioning Systems (GPS) has been found to be the most prevalent method to detect and tackle the extent of outbreaks during the pandemic. However, these services suffer from the inherent problems of infringement of data privacy that creates hindrance in adoption of the technology. Non-cellular wireless technologies on the other hand are well-suited to provide secure contact tracing methods. Such approaches integrated with the Internet of Things (IoT) have a great potential to aid in the fight against any type of infectious diseases. In response, we present a unique approach that utilizes an IoT based generic framework to identify individuals who may have been exposed to the virus, using contact tracing methods, without compromising the privacy aspect. We develop the architecture of our platform, including both the frontend and backend components, and demonstrate its effectiveness in identifying potential COVID-19 exposures (as a test case) through a proof-of-concept implementation. We also implement and verify a prototype of the device. Our framework is easily deployable and can be scaled up as needed with the existing infrastructure.

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