A Simplified and High Accuracy Algorithm of RSSI-Based Localization Zoning for Children Tracking In-Out the School Buses Using Bluetooth Low Energy Beacon
Open accessAbstract
To avoid problems related to a school bus service such as kidnapping, children being left in a bus for hours leading to fatality, etc., it is important to have a reliable transportation service to ensure students’ safety along journeys. This research presents a high accuracy child monitoring system for locating students if they are inside or outside a school bus using the Internet of Things (IoT) via Bluetooth Low Energy (BLE) which is suitable for a signal strength indication (RSSI) algorithm. The in/out-bus child tracking system alerts a driver to determine if there is a child left on the bus or not. Distance between devices is analyzed for decision making to affiliate the zone of the current children’s position. A simplified and high accuracy machine learning of least mean square (LMS) algorithm is used in this research with model-based RSSI localization techniques. The distance is calculated with the grid size of 0.5 m × 0.5 m similar in size to an actual seat of a school bus using two zones (inside or outside a school bus). The averaged signal strength is proposed for this research, rather than using the raw value of the signal strength in typical works, providing a robust position-tracking system with high accuracy while maintaining the simplicity of the classical trilateration method leading to precise classification of each student from each zone. The test was performed to validate the effectiveness of the proposed tracking strategy which precisely shows the positions of each student. The proposed method, therefore, can be applied for future autopilot school buses where students’ home locations can be securely stored in the system used for references to transport each student to their homes without a driver.
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Context-aware and semi-supervised calibration methods have been developed to adapt BLE ranging models to changing playground environments and to improve accuracy even when labeled training data are limited.
“Furthermore, context-aware and semi-supervised calibration methods have been developed to adapt BLE ranging models to changing playground environments and to improve accuracy even when labeled training data are limited [22,23].”
From Child Playground Entry/Exit Tracking and Log Visualization System Using BLE Beacons and Smart Devices (2026) · cites this paper as [22]
The Introduction describes a real-time modified RSSI method to mitigate signal fluctuations, and §2.1 describes fitting RSSI-model parameters from measurements to improve positioning accuracy. The setting is a school bus, not a changing playground; the paper does not describe context-aware or semi-supervised calibration or improved accuracy with limited labeled training data. Pages were not available in our copy. (LLM, conf=0.86)
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Chung, M. (2026) · Signals · doi:10.3390/signals7040067
“Furthermore, context-aware and semi-supervised calibration methods have been developed to adapt BLE ranging models to changing playground environments and to improve accuracy even when labeled training data are limited [22,23].”
- Authors
- Sakphrom, S., Suwannarat, K., Haiges, R., & Funsian, K.
- Affiliations
- Walailak University (TH)
- Institut Tadbiran Awam Negara (MY)
- Corresponding author
- Suwannarat, Korakot
- Funsian, Krit
- Venue
- Informatics
- Publisher
- MDPI AG
- Published
- 2021-09-25
- Volume
- 8
- Issue
- 4
- Pages
- 65
- ISSN
- 2227-9709 (ISSN-L)
- OpenAlex
- W3202355635
- Cited by
- 10
- References
- 22
- Citations by year
- 2026: 1 · 2024: 3 · 2023: 3 · 2022: 3
- FWCI
- 0.66
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Informatics (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Walailak University
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Indoor and Outdoor Localization Technologies
- Physical Sciences › Computer Science › Computer Networks and Communications › Bluetooth and Wireless Communication Technologies
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optical Wireless Communication Technologies
- Keywords
- RSSI-based localization, Bluetooth Low Energy beacons, LMS algorithm, trilateration, Internet of Things, kidnapping prevention
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