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GPSPiChain-Blockchain and AI based self-contained anomaly detection family security system in smart home

With advancements in technology, personal computing devices are better adapted for and further integrated into people’s lives and homes. The integration of technology into society also results in an increasing desire to control who and what has access to sensitive information, especially for vulnerable people including children and the elderly. With blockchain rise as a technology that can revolutionize the world, it is now possible to have an immutable audit trail of locational data over time. By controlling the process through inexpensive equipment in the home, it is possible to control whom has access to such personal data. This paper presents a block-chain based family security system for outdoor tracking and in-house monitoring of users’ activities via sensors to detect anomalies in users’ daily activities with the integration of Artificial Intelligence (AI). For outdoor tracking the locations of the consenting family members’ smart phones are logged and stored in a private blockchain which can be accessed through a node installed in the family home on a computer. The data for the whereabouts and daily activities of family members stays securely within the family unit and does not go to any third-party organizations. A Self-Organizing Maps (SUM) based smart contract is used for anomaly detection in users’ daily activities in a smart home, which notifies emergency contact or other family members in case of anomaly detection. The approach described in this paper contributes to the development of in-house data processing for outdoor tracking, and daily activities monitoring and prediction without any third-party hardware or software. The system is implemented at a small scale with one miner, two user nodes and several device nodes, as a proof of concept; the technical feasibility is discussed along with the limitations of the system. Further research will cover the integration of the system into a smart-home environment with additional sensors and multiple users, and ethical implementations of tracking, especially of vulnerable people, via the immutability of blockchain.

History

Publication title

Journal of Systems Science and Systems Engineering

Pagination

1-17

ISSN

1861-9576

Department/School

University College

Publisher

Springer

Place of publication

Germany

Rights statement

© Systems Engineering Society of China and Springer-Verlag GmbH Germany 2021

Repository Status

  • Restricted

Socio-economic Objectives

Artificial intelligence; Cybersecurity

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