Web-based reward and redemption system for smart recyle system

The Recycling rate among developing nation is very low and the number of waste is increasing every day.Although many steps have been taken such as through national campaign, yet the recycle rate remains unchanged especially in Malaysia.Thus, the smart recycle bin is proposed to give a reward to public user who thrown the recyclable waste into the innovated smart recycle bin by giving points (later can be converted to money).This paper discussed the development of reward-based smart recycle system.The system has been implemented in a web-based environment and it supports for public user and waste authority.The system is then to be integrated with the desktop-based applications for waste authority to manage the point and transaction from the innovated recycle bin to the reward system

Design and Simulation Study of Excitation Coil System with Different Array Configurations for Magnetic Particle Imaging Application

Magnetic Particle Imaging (MPI) is a tomographic imaging method has been introduced for three-dimensional (3D) imaging of human body with some potential applications such as magnetic hyperthermia and cancer imaging. It involves three important elements; tracer development using magnetic nanoparticles (MNPs), hardware realization (scanner using excitation and pickup coils), and image reconstruction optimization. Their combination will produce a high-quality image taken from any biological tissue in the human body based on the secondary magnetic field signal from the magnetized MNPs that are injected into human body. A homogeneous and adequate magnetic field strength from an excitation coil is needed to enhance the quality of the secondary signal. However, the complex surface topography of human body and physical properties of an excitation coil influence the strength and the homogeneity of the magnetic field generation at the MNPs. Therefore, this paper presents a new concept of excitation coil configuration to improve the magnetic field strength and the homogeneity to obtain better magnetization of MNPs to be detected in MPI. Two designs will be proposed with variation in physical properties and coil arrangement based on simulation study that will be carried out by using ANSYS Maxwell to generate magnetic field strength and homogeneity towards the targeted distance of 10 mm – 50 mm below the coils. The obtained magnetic field from the simulation was validated by the mathematical calculation using Biot-Savart Law equation. As a result, the new concept of excitation coil configuration proposed can be used to improve the MPI scanner system performance for various medical application

A simulation study of excitation coil design in single-sided mpi scanner for human body application

Magnetic particle imaging (MPI), a tomographic imaging method has been introduced for 3D imaging of human body with some potential applications such as magnetic hyperthermia and cancer imaging. It involves three important elements: tracer development using magnetic nanoparticles (MNPs), hardware realization (scanner using excitation and pickup coils), and image reconstruction optimization. Their combination will produce a high quality of image taken from any biological tissue in the human body based on the secondary magnetic field signal from the magnetized MNPs that are injected into human body. A homogeneous and adequate magnetic field strength from an excitation coil is needed to enhance the quality of the secondary signal. However, the complex surface topography of human body and physical properties of an excitation coil influence the strength and the homogeneity of the magnetic field generation at the MNPs. Therefore, this work focused on finding alternative design of excitation coil used in single sided MPI to produce up to 2 mT with high homogeneity of field distribution in the MNPs at the varied depth of 10 to 30 mm under the excitation coil. We proposed several designs with variation in physical properties and coil arrangement based on simulation study carried out by using Ansys Maxwell

Online Monitoring Water Level in Rainwater Harvesting (RWH) Storage Tank

Rainwater harvesting (RWH) system has gained recognition as one of the sustainable means to manage a water crisis in the future. Due to the increase of global population demand, problems related to the water scarcity slowly become a serious issue in Malaysia as well as other countries. The implementation of RWH system aims to supply adequate water resources to consumers with a significant reduction of costs. The significant economic savings of RWH is related to the rainwater tank capacity. Typically, the size of the rainwater harvesting system is determined based on the size of the roof catchment area and the rainfall data from the existing rain gauge. However, a problem arises when sometimes the dependency of design analysis on monthly rainfall data are likely to overestimate the sizing of water tank recommended for daily use. In this study, the integration between the RWH system and automatic water level detection was done to improve the current system of RWH. Water level detection system was installed in the rainwater storage tank to detect and monitor water level; hence, it will help to estimate the available water in the rainwater storage tank and to avoid any overdesign problems. The results showed that the automatic water level detection system operated efficiently during the one month with hourly output data

Intelligent approach to Force/Position Control of Ultrasound-Guided Breast Biopsy Robotic System

Large deformations occur inside the breast whenever the biopsy needle is inserted during conventional ultrasound-guided breast biopsy procedure. Inconsistent force from manual handling of the ultrasound transducer makes maintaining the suspected lump in the ultrasound-imaging region challenging and further position the patient at discomfort. Hence, this research presents the development of force controller for an ultrasound-guided breast biopsy (UGBB) robotic system in the aims to alleviate said issues by maintaining low contact force on the breast. A variant of force controllers has been studied; proportional (P), proportional and integral (PI), PID, PI-Fuzzy, Fuzzy-PID (F-PID), and Fuzzy-PID using Lookup Table (F-LUT) controllers. Effect of external disturbance such as subject respiration is considered to see the reliability of each developed force/position control system. Based on the simulation results, F-PID force controller shows promising outcome with a marginal error of 0.33% during the disturbance period and no error when the disturbance is absent

Detection and classification of moving objects for an automated surveillance system

Automated surveillance system has been the subject of much research recently. A completely automated system means a computer will perforin the entire task from low level detection to higher level motion analysis. Since conventional system practically using human power to monitor and did not applicable for a long hour monitoring, thus automated system had been created to replace the conventional system. This thesis focuses on a method to detect and classify a moving object that pass through the surveillance area boundary. Moving object is detected by using combination of two frame differencing and adaptive image averaging with selectivity. Technically, this method estimate the motion area before updates the background by taking a weighted average of non-motion area of the current background altogether with non-motion area of the current frame of the video sequence. This step had created a focus of attention for higher level processing and it helps to decrease computation time considerably. The output of a motion-based detector is essentially a collection of foreground that might correspond to the moving objects. But usually the output image produced from this process contaminated with noise and shadow. As a solution, morphological operation has been employed as an approach to remove noise from the foreground object. Mutual shadow that exists with the object had been abolished by combining chromatic colour values with lightness variable. Then, standardized moment invariant is employed to extract the features for each moving blobs. To recognize these blobs, the calculated moment values are fed to a support vector machine module that is equipped with trained extracted moment values for human and vehicle silhouettes. The system operates on colour video imagery from a stationary camera. It can handle object detection in outdoor environments and under changing illumination conditions. The applied post processing module capable to remove noise and shadow from the detected objects with less than 1% of error. Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. All the methods have been tested on video data and the experimental results have demonstrated a fast and robust syste

Detection and Classification of Moving Objects for an Automated Surveillance System

Automated surveillance system has been the subject of much research recently. A completely automated system means a computer will perform the entire task from low level detection to higher level motion analysis. Since conventional system practically using human power to monitor and did not applicable for a long hour monitoring, thus automated system had been created to replace the conventional system. This thesis focuses on a method to detect and classify a moving object that pass through the surveillance area boundary. Moving object is detected by using combination of two frame differencing and adaptive image averaging with selectivity. Technically, this method estimate the motion area before updates the background by taking a weighted average of non-motion area of the current background altogether with non-motion area of the current frame of the video sequence. This step had created a focus of attention for higher level processing and it helps to decrease computation time considerably. The output of a motion–based detector is essentially a collection of foreground that might correspond to the moving objects. But usually the output image produced from this iii process contaminated with noise and shadow. As a solution, morphological operation has been employed as an approach to remove noise from the foreground object. Mutual shadow that exists with the object had been abolished by combining chromatic colour values with lightness variable. Then, standardized moment invariant is employed to extract the features for each moving blobs. To recognize these blobs, the calculated moment values are fed to a support vector machine module that is equipped with trained extracted moment values for human and vehicle silhouettes. The system operates on colour video imagery from a stationary camera. It can handle object detection in outdoor environments and under changing illumination conditions. The applied post processing module capable to remove noise and shadow from the detected objects with less than 1% of error. Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. All the methods have been tested on video data and the experimental results have demonstrated a fast and robust syste

Development of Smart Wheelchair System for a User with Severe Motor Impairment

AbstractUsers with severe motor impairment may find it difficult to operate a wheelchair when they are in tight space (e.g., passing doorway) or when avoiding obstacles since they cannot command the wheelchair by means of a conventional joystick. Here we propose a framework that can assist users to overcome such circumstances using a hierarchical semi-autonomous control strategy. Initially multimodal user inputs based on momentary switch and yaw head angle are analyzed to decide a maneuvering mode and assign the direction of travel. Then, environmental information is perceived using the combination of a laser range finder and the Kinect sensor for determining safety map around wheelchair's vicinity. Eventually, the user's inputs are provided to the navigation planner along with the safety map to moderate motion that is collision free and the best for user preference. Experimental results demonstrate the feasibility of the proposed approach