<i>Retracted March 9, 2026:</i> AECT: Accurate Energy Efficient Contact Tracing Using Smart Phones for Infectious Disease Detection
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Post-publication record
- Nature
- Retraction
- Reason
- Compromised Peer Review;Concerns/Issues about Article;False/Forged Affiliation;Investigation by Journal/Publisher;Lack of Approval from Third Party;Misconduct by Third Party;Rogue Editor;
- Date
- 3/9/2026 0:00
- Flagged by OpenAlex?
- Yes
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Abstract
Contact tracing is an important technique to reduce the impact of infectious diseases in smart cities. Smart phones equipped proximity sensors can be used to enable contact tracing, however accuracy of detection and energy efficiency is a key challenge. To address this challenge, we propose an accurate energy-efficient contact tracing (AECT) algorithm that detects which users came in contact with an infected user by performing computations at the server-side. Additionally, the AECT algorithm uses the wireless scan method, which calculates proximity based on pseudo-range multilateration and makes relevant comparisons with the matching score (MS) method based on the computation of received signal strength indication (RSSI) metric. Simulation results demonstrate that the scan method (AECT) is highly accurate and outperforms the scan method, highlighting that real distance is a better metric in contact tracing than a proxy for distance such as RSSI. Lastly, simulation results also demonstrate that the scan method (AECT) is 16 times more energy-efficient than the baseline 1 Hz frequency method, and we recommend it as a method of choice for performing contact tracing against infectious diseases such as COVID-19.
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The record
- Venue
- ACM Transactions on Sensor Networks
- Topic
- COVID-19 Digital Contact Tracing
- Field
- Computer Science
- Canadian institutions
- École de Technologie Supérieure
- Funders
- —
- Keywords
- Computer scienceContact tracingComputationMetric (unit)Real-time computingTracingProxy (statistics)WirelessEnergy (signal processing)Wireless sensor networkArtificial intelligenceCoronavirus disease 2019 (COVID-19)AlgorithmInfectious disease (medical specialty)TelecommunicationsComputer networkEngineeringStatisticsMachine learningMathematics
- Has abstract in OpenAlex
- yes