SAIP2026

General Applications of High-Energy Physics Methods to Financial Systems and Distributed Sensor Networks

7 Jul 2026, 17:20

1h 20m

Great Hall (University of the Western Cape)

Poster Presentation Track B - Nuclear, Particle and Radiation Physics Poster Session 1

Speaker

Mr Tshepang Pule (University of the Witwatersrand, Johannesburg, Wits 2050, South Africa)

Description

High-energy physics (HEP) experiments operate in data-intensive environments
characterised by high event rates, complex detector systems, and the need to
extract rare signals from substantial backgrounds. This has led to the
development of robust methodologies for data acquisition, event selection,
statistical inference, and real-time data processing, particularly within
large-scale experiments at facilities such as CERN.

In this work, we investigate the general applicability of HEP-inspired data
analysis frameworks to non-physical systems, focusing on financial markets
and distributed Internet-of-Things (IoT) sensor networks as case studies.
Both domains produce continuous, high-volume data streams with significant
noise, non-stationary behaviour, and intermittent anomalous events,
presenting challenges analogous to those encountered in detector-based
experiments.

For distributed IoT sensor networks such as residential monitoring systems, we examine how detector-inspired techniques, including background estimation, noise filtering, and signal reconstruction, can be used to extract higher-level information from aggregated measurements. These approaches enable the identification of latent patterns within sensor data, including behavioural or value-related indicators inferred from otherwise low-level signals.