Numerical Simulations of THz Photoconductive Antenna

Terahertz (THz) (0.1 – 10 THz) region of the electromagnetic spectrum spans the frequency range between the mid-infrared and the millimetre range. THz technology has generated a lot of interest recently due to its potential applications as a tomographic imaging and material spectroscopic characterization technique in a wide range of industry sectors including aerospace industry, wood products industry, the pharmaceutical industry, art conservation and semiconductor industry. There have been significant advances in the development of THz sources and detectors. The radiated THz power from these devices, however, is very low, and they are very inefficient. Hence, there are still a lot of continued interests in developing more powerful and compact THz sources as this will enable new applications of this electromagnetic spectrum. In this thesis, a novel photoconductive antenna with an embedded electrode structure had been proposed. Formulated equations had been used with COMSOL Multiphysics software package for the proposed THz photoconductive antenna analysis. Simulation results indicate that the proposed THz antenna can store two times more effective electric energy than the conventional photoconductive antenna. These results suggest higher THz power could potentially be obtained using the proposed structure. The proposed model also exhibits almost double the value of current when the substrate material mobility is doubled. Based on the appraised parameters of the proposed model, the best dimension of a THz photoconductive antenna had been recommended to be constructed

Numerical Simulations of THz Photoconductive Antenna

Terahertz (THz) (0.1 – 10 THz) region of the electromagnetic spectrum spans the frequency range between the mid-infrared and the millimetre range. THz technology has generated a lot of interest recently due to its potential applications as a tomographic imaging and material spectroscopic characterization technique in a wide range of industry sectors including aerospace industry, wood products industry, the pharmaceutical industry, art conservation and semiconductor industry. There have been significant advances in the development of THz sources and detectors. The radiated THz power from these devices, however, is very low, and they are very inefficient. Hence, there are still a lot of continued interests in developing more powerful and compact THz sources as this will enable new applications of this electromagnetic spectrum. In this thesis, a novel photoconductive antenna with an embedded electrode structure had been proposed. Formulated equations had been used with COMSOL Multiphysics software package for the proposed THz photoconductive antenna analysis. Simulation results indicate that the proposed THz antenna can store two times more effective electric energy than the conventional photoconductive antenna. These results suggest higher THz power could potentially be obtained using the proposed structure. The proposed model also exhibits almost double the value of current when the substrate material mobility is doubled. Based on the appraised parameters of the proposed model, the best dimension of a THz photoconductive antenna had been recommended to be constructed

Palm Oil Soil Monitoring System for Smart Agriculture

Palm oil is among the first commodity in Malaysia. The production of palm oil can be increased by implementing smart agriculture technology. To produce a good quality of palm oil, good soil quality is vital. Lack of soil information can make it hard for the farmer to maintain the nutritious of the oil palm tree. Thus, a real-time palm oil soil monitoring system has been developed for Palm Oil Soil Monitoring in a Smart Agriculture. The system measured the pH, moisture and tilt of palm oil soil. These parameters were essential to determine the palm oil soil status of alkalinity, tilt and moisture. These sensors are connected to Arduino microcontroller, which captures, processes and analyses the data. The captured data will be sent via the WiFi connectivity to the cloud database for the record. Based on the data analysis, the quality of the soil will be determined for further action by the farmer. The results showed that the system had successfully processed, transmitted, displayed and concluded the soil’s status. As a result, real-time reading will be displayed in the graphical graph using ThingSpeak.&nbsp

IoT E-Waste Monitoring System to Support Smart City Initiatives

This project introduces the design and development of IoT E-waste monitoring system to support Green City initiatives in real-time. The main objective of this system is to design an IoT-based recycle e-waste monitoring system that will provide an efficient solution to electronics waste collection and generation data. The hazardous chemical components of e-waste have potentially adverse impacts on ecosystems and human health if not managed and monitored properly. Hence, the importance to constantly monitor the condition of the e-waste bin. The system measures and delivers up-to-date information to the system’s administrator on the waste level and bin’s current temperature in real-time. In case of fire, the system will give notification via its flame indicator. Agile Model is used as the research methodology as it offers an adaptive approach in respect to what features need to be developed. The proposed system consists of HC - SR04 Ultrasonic sensor which measures the waste level, a DS18B20 temperature sensor that detects the temperature in the bin, KY- 026 flame sensor, a Raspberry Pi 3 Model B+ as a microcontroller and ThingSpeak as an IoT web platform. ThingSpeak concurrently stores data for future use and analysis, such as prediction of the peak level of waste bin. This system is expected to increase the usage of e-waste recycle bin, hence supporting the Green City initiatives and creating a greener environment by monitoring and controlling the collection of e-waste smartly through the concept of Internet-of-Things (IoT)

SIEM Network Behaviour Monitoring Framework using Deep Learning Approach for Campus Network Infrastructure

One major problem faced by network users is an attack on the security of the network especially if the network is vulnerable due to poor security policies. Network security is largely an exercise to protect not only the network itself but most importantly, the data. This exercise involves hardware and software technology. Secure and effective access management falls under the purview of network security. It focuses on threats both internally and externally, intending to protect and stop the threats from entering or spreading into the network. A specialized collection of physical devices, such as routers, firewalls, and anti-malware tools, is required to address and ensure a secure network. Almost all agencies and businesses employ highly qualified information security analysts to execute security policies and validate the policies’ effectiveness on regular basis. This research paper presents a significant and flexible way of providing centralized log analysis between network devices. Moreover, this paper proposes a novel method for compiling and displaying all potential threats and alert information in a single dashboard using a deep learning approach for campus network infrastructure

Analysis of a Photoconductive Antenna using COMSOL

In this work we present numerical investigations of a novel terahertz (THz) photoconductive antenna with embedded electrodes using COMSOL Multiphysics software package. Simulation results indicate that the proposed THz antenna can store two times more effective electric energy than the conventional photoconductive antenna with planar electrode structures. These results suggest higher THz power could potentially be obtained using the proposed photoconductive antenna with embedded electrode structures

Requirements, Deployments, and Challenges of LoRa Technology: A Survey

LoRa is an ISM-band based LPWAN communication protocol. Despite their wide network penetration of approximately 20 kilometers or higher using lower than 14 decibels transmitting power, it has been extensively documented and used in academia and industry. Although LoRa connectivity defines a public platform and enables users to create independent low-power wireless connections while relying on external architecture, it has gained considerable interest from scholars and the market. The two fundamental components of this platform are LoRaWAN and LoRa PHY. The consumer LoRaWAN component of the technology describes the network model, connectivity procedures, ability to operate the frequency range, and the types of interlinked gadgets. In contrast, the LoRa PHY component is patentable and provides information on the modulation strategy which is being utilized and its attributes. There are now several LoRa platforms available. To create usable LoRa systems, there are presently several technical difficulties to be overcome, such as connection management, allocation of resources, consistent communications, and security. This study presents a thorough overview of LoRa networking, covering the technological difficulties in setting up LoRa infrastructures and current solutions. Several outstanding challenges of LoRa communication are presented depending on our thorough research of the available solutions. The research report aims to stimulate additional research toward enhancing the LoRa Network capacity and allowing more realistic installations

Preliminary study: Readiness of WLAN Infrastructure at Malaysian Higher Education Institutes to support Smart Campus Initiative

Smart campus initiative enables higher education to enhance services, decision-making, and campus sustainability. The initiatives are being actively implemented globally by higher education, including in Malaysia. The recent COVID-19 pandemic has underscored the need for the education sector to explore a digital revolution. The adaptation of digital technologies has improved many aspects, including the teaching and learning experiences and administration tasks, which results in more efficient task handling. This study investigates the readiness of the WLAN infrastructure at Malaysian Public Higher Education Institutes (HEIs) in implementing smart campus initiatives and measures readiness based on the availability of WLAN Infrastructure, WLAN logical architecture and WLAN populated coverage area. This study administered a questionnaire to 19 respondents, all of whom are IT personnel from Malaysian public HEIs to gather preliminary data on the readiness of WLAN infrastructure at Malaysian Public HEI to support the adaptation of smart campus initiatives in their teaching and learning activities. This study is a preliminary study concerning the readiness of WLAN infrastructure at Malaysian Public HEI in adapting smart campus initiatives. The findings show that, even though WLAN service is available at all Malaysian Public HEI, it is essential to enhance the adopted logical architecture and WLAN coverage to prepare HEI to become smart campuses. The findings of this study can provide the fundamental guidelines for the Ministry of Higher Education in determining the baseline of WLAN infrastructure required by Malaysian HEI to support smart campus initiatives

A novel deep learning technique to detect electricity theft in smart grids using AlexNet

Electricity theft (ET), which endangers public safety, interferes with the regular operation of grid infrastructure, and increases revenue losses, is a significant issue for power companies. To find ET, numerous machine learning, deep learning, and mathematically based algorithms have been published in the literature. However, these models do not yield the greatest results due to issues like the dimensionality curse, class imbalance, inappropriate hyper-parameter tuning of machine learning, deep learning models etc. A hybrid DL model is presented for effectively detecting electricity thieves in smart grids while considering the abovementioned concerns. Pre-processing techniques are first employed to clean up the data from the smart meters, and then the feature extraction technique, AlexNet is used to address the curse of dimensionality. An actual dataset of Chinese smart meters is used in simulations to assess the efficacy of the suggested approach. To conduct a comparative analysis, various benchmark models are implemented as well. This proposed model achieves accuracy, precision, recall, and F1-score, up to 86%, 89%, 86%, and 84%, respectivel