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This study delves into the pivotal role of chassis design within Unmanned Ground Vehicles (UGVs), a cornerstone housing various components critical to the UGV's operational functionality. The context of this investigation pertains to the UGV's deployment in environments necessitating resilience against external stresses, while proficiently navigating uneven terrains with low traction. This segment meticulously documents and examines the design process to create a chassis that aligns with the project's requisites. [ABSTRACT FROM AUTHOR]

The oil palm plantation industry heavily relies on foreign labour for harvesting, particularly for collecting loose fruits (LF) alongside fresh fruit bunches (FFB). Manual LF collection, involving bending and repetitive movements, not only diminishes productivity but also poses health risks to workers. This study proposes an automated LF collector to mitigate these challenges. The developed system integrates an LF picker with a robot arm, an LF detector using image processing and a camera, a GPS-based human-follower vehicle, a back-to-home navigation system based on weight detection, and an obstacle avoidance system. The automated LF collector aims to operate autonomously, reducing workforce reliance and enhancing productivity in oil palm plantations. The study discusses the motivation, challenges, and objectives of developing such a system, emphasizing its potential economic and societal benefits. Additionally, the implementation of a novel image processing technique, Faster Objects More Objects (FOMO), using a neural network, is detailed for efficient LF detection. The proposed automated LF collector addresses labour shortages, enhances economic productivity, and reduces the risk of worker injuries in the oil palm industry. [ABSTRACT FROM AUTHOR]

The presented study focuses on the development of a dumping platform utilizing hydraulic and servo arm mechanisms. The platform serves as a site for dumping collected oil palm fruits by an Unmanned Ground Vehicle (UGV) within an oil plant estate. The investigation is guided by existing research and design principles from various sources, highlighting the mechanics of hydraulic scissor lifts and servo motor control. The prototype employs recycled plywood, surgical syringes, and servo motors to demonstrate its functionality, though acknowledging limitations of plywood in terms of strength and durability. The results showcase the successful lifting of the UGV and tilting of the dumping bucket. The study offers valuable insights into the design considerations and mechanics involved in creating an efficient and environmentally friendly dumping platform. [ABSTRACT FROM AUTHOR]

This project proposes the design of a GPS-based autonomous vehicle for the purpose of navigation and following operators in the collection of loose fruits in oil palm plantations. The aim is to reduce the burden on operators who traditionally must manually collect the loose fruits while following behind a truck. The proposed autonomous vehicle utilizes a GPS module to track its real-time location and follows the operator based on their smartphone's GPS coordinates. The vehicle's navigation is controlled by calculating displacement, bearing, and heading angles using GPS coordinates and a digital compass. The vehicle's movement is determined by the heading-to-bearing ratio, allowing it to move forward, turn left or right, or stop depending on the ratio value. The proposed design includes the selection of appropriate components such as GPS module, digital compass, Bluetooth module, motor driver module, and Arduino Mega 2560 microcontroller. The circuit diagram and prototype of the vehicle are presented. The working principle of the vehicle involves point-to- point navigation, calculation of displacement and bearing angles, and utilization of a digital compass for heading determination. The system has been tested and the results show successful navigation and movement of the vehicle based on the operator's location. However, improvements are needed for real-life deployment and extended operation duration. Overall, the GPS-based autonomous vehicle presents a promising solution for efficient and automated loose fruit collection in oil palm plantations. [ABSTRACT FROM AUTHOR]

This research delves into the intricate realm of electrical and power management for a prototype Unmanned Ground Vehicle (UGV), encompassing the configuration of circuitry, wire connections, and power dissipation calculations. Leveraging insights from past journal articles, this study selects electronic components based on their attributes, advantages, and drawbacks. The chosen components are then seamlessly integrated into the UGV's General- Purpose Input/Output (GPIO) pin layout, forming an interconnected web of functionality. The UGV's physical arrangement is meticulously crafted to fit within the chassis confines while ensuring a protective casing encapsulates and safeguards all components and wires. [ABSTRACT FROM AUTHOR]

The palm oil industry in Malaysia has undergone a significant transformation with the adoption of mechanized equipment to streamline the process of fresh fruit bunch (FFB) collection. Traditionally, manual labour-intensive techniques were employed, requiring workers to climb trees for bunch cutting and transportation. The introduction of mechanical buffaloes or harvesters equipped with hydraulic arms has revolutionized the FFB collection process. This paper explores the evolution of hydraulic arms, focusing on innovations such as articulated arms and computer-controlled robotic arms that enhance efficiency, precision, and safety. The replication of this technology through a robotic arm emphasizes data utilization, assembly, and functionality. Additionally, the study delves into the broader implications of mechanization in the palm oil industry, addressing challenges and opportunities for increased productivity and reduced labour costs. The adoption of automated harvesting techniques holds the potential to improve palm oil production, but careful consideration of specific farm needs, along with the advantages and challenges of mechanization, is essential in making informed decisions. [ABSTRACT FROM AUTHOR]

Interests in doing a degree in engineering is waning. There are several reasons as to why this is occurring from one blaming the low entry point salary for a fresh engineering graduate to the fact that some high-school leavers are more interested in the gig economy. Whatever the reason, it is undeniable that the engineering profession as well as the needing of engineers will never wane, thus there is a need for those of us who can, should continue to enhance awareness about engineering as a viable, lucrative and sustainable profession to those in high-school, enhancing their interest in the subject matter. To further peak this interest, an attempt was made to develop an engaging programme, which involved a succinct and quick design and build experience to show prospective students what studying engineering is all about. The programme was developed with this in mind and at the end of it, close to 25% of all participants indicated an interest in engineering upon the end of the programme (a growth of 15% which was found from a survey done prior to the programme starting). This paper aims to share how this programme was developed and the results of the survey from the programmes participants. [ABSTRACT FROM AUTHOR]

The efficiency of automated palm oil harvest collecting machines is a critical factor in the agricultural industry. This project delves into the essential process of calculating the arm capacity in these machines, which directly impacts their fruit collection capabilities. Through a combination of measurements and calculations, including factors like arm dimensions, fruit weight, and volume, this report equips industry professionals with valuable insights for selecting the most suitable equipment. It also explores the broader context of automated fruit harvesting technologies, highlighting their potential to revolutionize the agriculture sector. With a focus on precise calculations and an understanding of engineering principles, this project lays the foundation for improved operational efficiency and informed decision-making in the world of automated palm oil harvest collection. [ABSTRACT FROM AUTHOR]

Markforged Onyx is a composite material that has gained significant attention in recent years due to its unique properties and applications in 3D printing technology. In this paper, we provide a comprehensive review of the research and developments related to Markforged Onyx, including its composition, mechanical properties, and potential applications in various industries. We examine the advantages and limitations of using Markforged Onyx in 3D printing and compare it to other materials commonly used in the field. We also discuss the various techniques and parameters used in 3D printing with Markforged Onyx, including the effects of layer thickness, printing speed, and infill density on part quality and strength. Finally, we highlight some of the key challenges and opportunities for future research related to Markforged Onyx and provide recommendations for the optimization and expansion of its use in various applications. Overall, this paper aims to provide a comprehensive overview of Markforged Onyx and its potential as a leading material in the field of 3D printing. [ABSTRACT FROM AUTHOR]

In this project, five essential sections were developed, spanning from the investigative phase to implementation. Each segment, including data collection and transmission, cloud connectivity, AGV Wi-Fi vehicle, fertilizing mechanism, and data analytics, was meticulously crafted based on selected tools and methodologies. NodeMCU ESP8266 was chosen as the microcontroller for data collection and transmission, successfully executing tasks of receiving and transmitting data to the cloud server. Google Sheet was employed as the cloud service provider due to its suitability for the project, with advantages over other platforms discussed. The workflow of the Wi-Fi controlled vehicle and cloud connectivity was elucidated through block diagrams, and the decision tree function was detailed using flowcharts. The successful system implementation and results were showcased. For data analytics, Microsoft Power BI software was selected for its user- friendly interface. The connection between Google Sheet and Power BI was outlined in a block diagram, and step-by-step instructions for observing data analytics results were provided through flowcharts. The Power BI results and dashboards were presented in the system implementation section, emphasizing the comprehensive approach taken in this project. [ABSTRACT FROM AUTHOR]

The presented study focuses on the development and integration of a smart fertilizing system, comprising data collection, cloud connectivity, AGV Wi-Fi vehicle, fertilizer mechanism, and data analytics. This chapter provides a detailed explanation of the integrated system, featuring prototype designs and circuit diagrams for enhanced comprehension. The circuit diagram delineates two key sections: plantation monitoring devices and smart fertilizing vehicles, elucidating activity sequences through block diagrams and flowcharts. Comprehensive testing results are presented to demonstrate the system's functionality, aiding in the identification of optimal fertilizing routes for the AGV Wi-Fi vehicle within the plantation. Furthermore, the integrated system is bolstered with cloud connectivity, enabling precise fertilizer dispensing based on nutrient levels in specific areas. This modification ensures comprehensive coverage of nutrient-deficient regions, enhancing the system's efficiency and feasibility in fertilizing all oil palm trees effectively. [ABSTRACT FROM AUTHOR]

This study focuses on using a special sensor to figure out if palm fruits are ready to be picked. Usually, people look at the color of the fruits or count how many have come loose from the tree to know if they're ripe. But because there aren't enough workers, sometimes the fruits become too ripe before they're picked. So, this study suggests using a color sensor to check the fruit's color and decide if it's ready. Other research like "Segregation of oil palm fruit ripeness using color sensor" (2022) used a color sensor and a small computer to sort ripe and not ripe palm fruits. Similarly, "Application of Colour Sensor in the Determination of Tomato Fruit Ripeness" (2019) made a tool to sort ripe and not ripe tomatoes using a color sensor and a small motor. "Information System Prototyping of Strawberry Maturity Stages" (2020) used a color sensor and a small computer to find out if strawberries are ripe and showed results on a webpage. This research could help palm oil farms work better by using color sensors to decide if fruits are ripe. [ABSTRACT FROM AUTHOR]

The purpose of these investigations is to help palm oil farms in determining when their produce is ready for harvest. For large farms, this is a major issue because it is laborious to manually separate ripe from unripe fruit. During its training phase, the sophisticated system they used (called YOLOv5n) performed excellently. Testing carried out in real time demonstrated its ability to distinguish between ripe and unripe palm oil fruits from a reasonable distance. The study also investigates other approaches people are taking using technology like micro controllers and cameras with advanced features to reach this objective. This system functions as a helpful tool, allowing farms to save both time and money. Comparable to an innovative fruit picker. [ABSTRACT FROM AUTHOR]

The effective use of modern technology is proving useful when compared to contemporary agricultural practices observed in areas such as Southeast Asia and the Middle East. This study investigates the palm oil business in Malaysia, an important contributor to the nation's economy, which must deal with a challenge faced by the Red Palm Weevil (RPW). The timely detection of Red Palm Weevil (RPW) infections has a major effect, and this study investigates a device that utilizes an accelerometer to detect vibrations induced by RPW. The results indicate that the above-mentioned strategy is effective in detecting RPW difficulties at an early stage, therefore delivering a lot of help to the farming industry and other related fields. [ABSTRACT FROM AUTHOR]

This research proposes an automated sensory system that uses the Blynk IoT platform to monitor the production of palm tree oil. The system incorporates temperature, humidity, and soil moisture sensors to gather vital environmental data. The Blynk platform receives this data wirelessly, allowing for real-time analysis and visualization. Using this approach gives palm tree growers the ability to maximize fertilizer and irrigation, improving the quantity and quality of their oil. This technology is beneficial for effective plantation management because of the Blynk platform's user-friendly interface and the expanding role of IoT in agriculture. [ABSTRACT FROM AUTHOR]

This research focuses on palm fruit harvesting using data from Internet of Things (IoT) technologies. Alternatives to relying on error, one can might consider using sensors for tracking. However, advanced sensors can be expensive. Therefore, we are considering cheaper options with simplified sensors. One form detects movement, while the other detects pressure. These choices could simplify fruit counting without spending much. Our research involves past studies, understanding parts, and how they connect. [ABSTRACT FROM AUTHOR]

This research introduces a user-friendly AI system designed to improve palm oil plantations. The system monitors the plantation's environment using sensors and provides helpful recommendations for irrigation schedules, pest control, and tree health. By analysing historical data and weather conditions, the AI system can predict future trends and guide decision-making. The main purpose is to increase efficiency, productivity, and cost-effectiveness for a thriving and sustainable palm oil plantation. [ABSTRACT FROM AUTHOR]

This paper aims to develop a smart solution for powering operations in palm oil plantations without traditional power sources. Batteries step in due to the absence of electrical outlets, managed by an Arduino Uno. Various sensors and devices draw power from these batteries. To tackle battery life concerns, a battery management approach is explored, investigating different battery types and power-saving methods like sleep down modes. Research involves into power bank compatibility with Arduino and strategies to minimize sensor power usage. Rechargeable batteries like power banks and 9V options are favored over solar. Sleep mode integration, triggered by motion sensors, aids energy efficiency, enhancing battery life. [ABSTRACT FROM AUTHOR]

The integration of Internet of Things (IoT) technology into a palm fruit ripeness detection system is the focus of this part of the paper. IoT's remote control and monitoring capabilities are pivotal for sensor-driven setups. In the palm oil industry, where conventional fruit ripeness assessment methods are inefficient, IoT emerges as a solution. Notably, platforms like Blynk and technologies like LoRaWAN are instrumental. Blynk facilitates streamlined device connectivity and management, while LoRaWAN's extensive coverage suits large agricultural areas. A practical prototype integrating Arduino and Node MCU ESP8266 showcases IoT's potential in optimizing agricultural practices. [ABSTRACT FROM AUTHOR]

This paper investigates the global use of palm oil, particularly in Malaysia and Indonesia. The palm oil industry faces losses due to a lack of workers causing delays in harvesting fresh fruit bunches (FFBs). To address this, a device is developed using falling fruits to gauge their ripeness. The literature review explores factors contributing to oil losses and how FFB ripeness impacts oil quality. It also examines mechanical fruit harvesting. The process of selecting materials and components for the prototype is explained. The prototype's implementation involves fixing it to palm trees to catch falling fruits. In conclusion, this research offers a solution to the problem of labour shortage-related losses in the palm oil industry by utilizing falling fruits to determine ripeness, potentially benefiting the industry's productivity and financial stability. [ABSTRACT FROM AUTHOR]

The use of computational modelling to study the cardiovascular system has a great deal of potential, but it is also a significant problem that calls for expertise in a wide range of disciplines. This article's goal is to present a synopsis of the most current developments that have been made in the field of cardiovascular structural modelling. These developments include the development of numerical techniques, primary constitutive models, and modelling methodologies that can describe cardiovascular structures and diseases throughout a wide range of length and timelines. The purpose of this article is to act as an approachable point of reference for those who are new to the topic. The presentation begins with a general review of the models were first developed for one application and scale may be utilised for an expanding variety of applications that are quite similar to one another. [ABSTRACT FROM AUTHOR]

The development of a system that can detect falls is the primary focus of this research. According to the background study, the most major reason of injuries as well as fatalities that occur during the construction for high rise buildings are falls that do not get the timely and appropriate medical treatment that they need. This research presented a system for falling detection that is both reliable and efficient, with the goal of detecting falls and notifying relatives so that they may provide assistance and support. The appropriate authorities have been made aware of the situation via the use of an alert mechanism in the form of a Short Message Service (SMS). In addition to this, the deployment of this wearable gadget is less expensive and it offers a prompt reaction. The sensitivity as well as specificity of our fall detection are respectively 95% and 90%. [ABSTRACT FROM AUTHOR]

The research described in this paper outlines the comprehensive development process of a system spanning five key sections: data collection and transmission, cloud connectivity, AGV Wi-Fi vehicle, fertilizing mechanism, and data analytics. The investigation involved the careful selection of tools and techniques for each section, with a focus on NodeMCU ESP8266 as the microcontroller for data collection and transmission, utilizing various sensors. Google Sheet was chosen as the cloud service provider due to its suitability for the project, and a detailed comparison of platform advantages was provided. The workflow of the WIFI controlled vehicle and cloud connectivity was elucidated through block diagrams and flowcharts. The system implementation successfully integrated Google Sheet with Microsoft Power BI for data analytics, leveraging its user-friendly interface. The connection setup between Google Sheet and Power BI was illustrated, and a step-by-step guide for interpreting data analytics results was presented. The paper concludes by showcasing the implemented system and displaying the Power BI dashboard, demonstrating the practical application of the developed solution. [ABSTRACT FROM AUTHOR]

This project presents an integrated smart fertilizing system designed to tackle challenges in the oil palm industry. A thorough literature review explored key components such as data collection, cloud connectivity, AGV Wi-Fi vehicles, fertilization mechanisms, and data analytics. The methodology involved system integration, enhancement, and field testing in a palm estate, adhering to rigorous engineering standards, sustainability principles, and efficient project management. The project, costing RM245.30, successfully met its objectives during field tests, offering a promising solution for issues in the oil palm sector. [ABSTRACT FROM AUTHOR]

The encryption strength and compression efficiency are sometimes two opposing concepts in simultaneous picture compression and encryption methods. In this research, we suggest a novel lossy JPEG-based combined picture compression and encryption strategy that strives to increase encryption capability while preserving JPEG's compression efficiency. A covert orthogonal transform encrypts an original picture as a collection of coefficients. Since the image has a sparse representation in the conventional transform domain, it can be reconstructed from a small number of measurements, and thus allows the encrypted picture data to be compressed into a collection of measurement data. A secondary encryption approach based on the Fourier transform is used to a series of photographs to further strengthen their security. In addition, a fractional-order chaotic system with more complex chaotic behavior is constructed for application in picture compression and encryption. From what we can tell from experiments, the algorithm is robust and secure. First, we employ content-adaptive interpolation to acquire missing bitplanes and rejected pixels in order to rebuild the original picture. The first three MSBs are recovered losslessly by a combination of LDPC decoding, decryption, and Markov random field (MRF) exploitation. [ABSTRACT FROM AUTHOR]

The farming industry has an important part in Malaysia's economy, making a substantial contribution to its gross domestic product (GDP) and contributing as a major source of employment for a significant section of the general population. However, the life expectancy of oil palm trees, which are necessary for the cultivation and extraction of palm oil, could be reduced due to insufficient soil conditions. A real-time smart agriculture system was developed with the aim of helping farmers. The system utilizes sensors and Wi-Fi connectivity to gather and transmit data regarding soil conditions to a cloud-based platform which can be accessed through an application for smartphones. This technology provides farmers with accurate data at all times, therefore enhancing their decision-making capabilities and expanding oil palm profitability. The research being investigated shows the possibility of larger implementation in the field of the agriculture industry. [ABSTRACT FROM AUTHOR]

Convolutional neural networks are proposed as an automated method for segmenting nasopharyngeal carcinoma (NPC) from dual-sequence magnetic resonance images (MRI). Each of the 44 NPC patients had an MRI scan done using the T1-weighting (T1W) and T2-weighting (T2W) techniques. Nasopharyngeal carcinoma, or NPC, is a disease that is quite common in several places, including South China, the Middle East, and Southeast Asia. The most successful kind of treatment for this malignant tumour has been radiation therapy. Using an updated network based on 3D Unet (AUnet), organ size is integrated as prior information into the convolutional kernel size design, and end-to-end training is employed to increase modelling efficacy. This enhances the performance of the model by allowing the network to adaptively harvest traits from organs of various sizes. To increase modelling efficacy, end-to-end training and a better network based on 3D Unet (AUnet) are used. To gauge the effectiveness of the AUnet network, the Dice Similarity Coefficient (DSC) coefficients and Hausdorff Distance (HD) distances of both automatic and manual segmentation are examined. Based on its characteristics, a tumour may be identified, separated from the liver, and finally assessed to identify the cancer's stage. As a result, the process can be divided into three separate phases: Segmentation by region, segmentation by liver tumour, and stage detection of cancer are the first three. In order to analyse a liver tumour and detect it at an early stage, this research article offers the findings of an examination into the various methods for segmenting the liver area and tumour on an abdominal CT scan. In this review, each of these facets is broken down and studied, and a comparison of the different techniques is carried out. The authors of this research came to the conclusion that despite the hopeful outcomes that automated systems have produced, their performance is still a long way off from the results that may be achieved by manually delineating tumours. [ABSTRACT FROM AUTHOR]

Kidney is a vital part of the body's metabolic process and a key toxic waste removal mechanism. The blood filtering procedure known as hemodialysis is performed in individuals with severe renal failure. By pushing a patient's blood against a fluid combination called dialysate, a dialysis machine performs hemodialysis. This study seeks to build a prototype design of a Hemodialysis Dialysate Temperature Control System to lessen the risk of patients experiencing temperature shock during hemodialysis treatment since the dialysis machine has problems maintaining the proper temperature of dialysate. To achieve a body temperature of (36⁰C) for patients, two different temperatures of the dialysate were combined with various flow rates. One temperature of the dialysate was maintained below body temperature (35⁰C), and the other was kept above human body temperature (37⁰C). The results show the desired output temperature of 36⁰C is achievable by using fuzzy logic-based controller. The system will give an approximate constant output of desired temperature with a time taken of 670 seconds where the output volume for each circulation is 50 ml/s. The hemodialysis dialysate temperature control system prototype with the implement of fuzzy logic shows that the system consumes time for heating but is able to give a close by to constant desired output temperature. [ABSTRACT FROM AUTHOR]

Effective ventilation is vital for indoor air quality and occupant comfort. However, room layout and furniture placement can influence ventilation distribution, leading to inconsistent airflow. This study investigates the relationship between ventilator placement and ventilation profiles in a room. Experimental simulations were performed using the computational fluid dynamics (CFD) with varying placements of ventilator fans were conducted. The 8 different placements were made at high and medium height configurations across the walls either opposite or perpendicular to the inlet section in the enclosed space which in this case, is a room. The boundary conditions set at ambient atmospheric pressure of 101325 Pascals and the ambient temperature is set at a room temperature of 293.2 K. The results show that ventilator placement significantly affects ventilation distribution, with some areas experiencing inadequate or inconsistent airflow and ventilation coverage. The results obtained had determined that the higher placement of ventilator and located strategically at the opposite of the inlet section would be the most optimized configuration where the air flow will have a more complete distribution and coverage of the space in the enclosed space. These findings would promote better room designs to optimize ventilation and enhance occupant comfort. [ABSTRACT FROM AUTHOR]

Prospective students who have been diagnosed with autism may lie along the breadth of the autism spectrum. The spectrum itself is wide, consisting of neurodivergent individuals as well as ranging from those who are non-verbal or otherwise. Generally speaking, neurodivergent individuals with autism are diagnosed with having autism spectrum disorder are classified as mild, mild-moderate, moderate, moderate-severe and severe. These classifications stretch across the autism spectrum and may also include individuals with behavioral challenges and hence are individuals with high needs, requiring elevated levels of care from those of us who are aptly experienced and neurotypical. There is little literature, particularly within the Asian region, on how engineering education increases its inclusivity, extending such programmes to prospective students who are autistic. It is unclear whether such engineering undergraduate programmes, in its current forms, may be open to those who are mild, moderate, or other classifications. Information is also scarce in terms of how engineering education as a whole may be further evolved to include such individuals. This paper attempts to share current efforts on how engineering education aims to increase inclusiveness for individuals who have been diagnosed with autism. [ABSTRACT FROM AUTHOR]