CoChat
Sign Up
Cited by 1IoT and Edge/Fog ComputingInternet of Things and AIDigitalization, Law, and Regulation

AI-Enabled Low-Power IoT for Child Safety in Schools: A Legal-Technical Framework for Sustainable Protection

Mallick, Navonita, Nanda, Hiranmaya, Sahu, Shashwata, Pattnayak, Parthasarathi, Mohanty, Arpeeta, Das, Tulip·2026·2026 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)
DOI 10.1109/iatmsi68868.2026.11466166
Open this paper in CoChat — free account

Abstract

Child safety in schools is a major global challenge. UNICEF estimates 246M children face violence or safety threats annually, and WHO reports 115,000 child deaths from unintentional injuries in school or commuting contexts. This paper investigates AI-enabled, low-power IoT for child tracking and safety, integrating wearable sensors, edge-AI anomaly detection, and energy-aware communications. Using a literature-based analytical method, we synthesise UNICEF/WHO evidence, IEEE standards, and multijurisdictional legal frameworks to propose a layered technical legal model that embeds consent, minimization, encryption, and retention into system design. The framework targets real-time, event-driven protection with lower energy and bandwidth needs than legacy surveillance, balancing efficiency with rights-based governance. We consolidate secondary case evidence indicating evidence of improvements in energy efficiency, response times, and false-alarm rates. We outline a phased roadmap and evaluation metrics for pilots in diverse school settings.

Integrity signals

Registry

Crossref · 10.1109/iatmsi68868.2026.11466166

Cites

25 of 25 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Many studies emphasize localization accuracy in classrooms, school buildings, or laboratory-like indoor testbeds.

    “Second, many studies emphasize localization accuracy in classrooms, school buildings, or laboratorylike indoor testbeds, whereas relatively few provide empirical validation in semi-open playground environments where children move actively and line-of-sight is frequently interrupted [8].”

    From Child Playground Entry/Exit Tracking and Log Visualization System Using BLE Beacons and Smart Devices (2026) · cites this paper as [8]

  • Relatively few studies provide empirical validation in semi-open playground environments where children move actively and line-of-sight is frequently interrupted.

    “Second, many studies emphasize localization accuracy in classrooms, school buildings, or laboratorylike indoor testbeds, whereas relatively few provide empirical validation in semi-open playground environments where children move actively and line-of-sight is frequently interrupted [8].”

    From Child Playground Entry/Exit Tracking and Log Visualization System Using BLE Beacons and Smart Devices (2026) · cites this paper as [8]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Mallick, N., Nanda, H., Sahu, S., Pattnayak, P., Mohanty, A., & Das, T.
Affiliations
KIIT University (IN)
ORCID
Venue
2026 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)
Publisher
IEEE
Published
2026-03-12
Pages
1-6
DOI
10.1109/iatmsi68868.2026.11466166
OpenAlex
W7151548274
Cited by
0
References
25
FWCI
0.00
Type
conference paper
Language
en
Open access
closed
Licence
Locations
IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
  • Social Sciences › Law › Digitalization, Law, and Regulation
Keywords
low-power IoT, child tracking, wearable sensors, energy-aware communication, data protection law, consent, data minimization, encryption, data retention, false alarm rate

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review