https://www.um.edu.mt/library/oar/handle/123456789/143802 2026-08-24T08:44:44Z https://www.um.edu.mt/library/oar/handle/123456789/148120 Title: The development of a B-Train system for the CERN proton synchrotron booster Abstract: In particle accelerators, large electromagnets generate the perpendicular magnetic field that dictates the beam trajectory based on the Lorentz force law. Therefore, precise knowledge of the integrated dipole field produced by these accelerator-magnets is essential for transverse and longitudinal beam control. Consequently, machine operators rely on look-up tables, prediction models, or online measurement systems, called B-Trains, to acquire and distribute the magnetic dipole field in real-time. At the European Organization for Nuclear Research (CERN) accelerator complex, all synchrotrons have been fitted with a new standardised B-Train setup as part of a site-wide consolidation project. This so-called Field In REal-time STreaming from Online Reference-Magnets (FIRESTORM) system has been developed in-house to accommodate the various requirements of the six different machines. One such machine is the Proton Synchrotron Booster (PSB), which was constructed in the 1970s and has undergone several upgrades to meet the ever-increasing demand for higher energies. The most recent upgrade, which occurred in 2020, enabled the PSB to accelerate beams up to 2.0 GeV every 1.2 s. This thesis deals with the work involved in implementing the new B-Train setup for the main-bending-magnets of the PSB. The first part provides an overview of the new FIRESTORM system, detailing its architecture and the operating principle behind several components. The results of a metrological characterisation of its offline performance are also provided, including drift correction, gain calibration and frequency response, in addition to the overall latency of its distribution network. Furthermore, the FIRESTORM system underwent an online qualification campaign to compare its capabilities with the previous Legacy setup. The second part focuses on the calibration process of the induction-coils. It is well known that saturation of the yoke affects the longitudinal field profile of an acceleratormagnet and, by extension, the measurement accuracy. Therefore, this thesis presents a novel measurement method developed for measuring fast-pulsed magnetic fields using the Single Stretched Wire (SSW) system. Being the reference standard, the SSW is commonly used to measure steady-state magnetic fields with absolute precision. This new procedure expands the capabilities of the SSW setup, enabling accurate measurements of timevarying magnetic fields in addition to those at steady-state. Furthermore, this work also proposes a magnetic model that characterises the quasi-static and dynamic responses of iron-dominated bending-magnets. The model presents a method for predicting eddy-currents as a summation of response-functions. Using the PSB main-bending-magnet as a test case, the model successfully replicates the transfer-function with a relative accuracy of less than 200 ppm. Description: Ph.D.(Melit.) 2025-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/144078 Title: Adoption of the LoRa transmission protocol for a low power indoor air quality monitoring system Abstract: Indoor air quality (IAQ) is a critical, often-overlooked public health concern, driving the need for robust Internet of Things (IoT) monitoring systems to optimise building ventilation and energy efficiency. This research addresses two major gaps: the high power consumption of existing wireless sensor nodes and the lack of cost-effective, scalable big data systems for large-scale IAQ monitoring. The core contribution is an ultra-low-power, low-cost wireless sensor node integrating state-of-the-art (SOA) sensors for carbon dioxide, volatile organic compounds, particulate matter, temperature, humidity, and pressure. Utilising dynamic power management, a sleep mode current draw of 270 nA and an average active current of 38 mA is achieved. This translates to an overall energy consumption of approximately 327 μAh per hour, and a projected battery life of 40 months on a 10,500 mAh battery. The achieved power efficiency is significantly better than both comparable academic and commercial SOA devices, even while offering a broader range of sensing capabilities. Complementary to this, the work introduces a cost-effective, LoRa-based big data system for large-scale IAQ monitoring. This system features a novel data forwarding server that calculates Air Quality Index (AQI) and Thermal Comfort Index (TCI) values, storing the enriched data in a document-oriented database. The research also validated a theoretical simulation model for indoor LoRa propagation. Advanced data visualisation was also developed, including a coordinate-based AQI heatmap, enabling smarter building management system (BMS) control. This research establishes a new benchmark for ultra-low-power, modular IAQ technology, coupled with a proven, scalable big data solution, accelerating the adoption of high-density IoT for healthier, smarter buildings. Description: Ph.D.(Melit.) 2025-01-01T00:00:00Z