Abdul Halim Ismail
Thumbnail Image
Preferred name
Abdul Halim Ismail
Official Name
Ismail, Abdul Halim
Main Affiliation
Web Site
Scopus Author ID
55210077800

Research Output

Filters

11
Show more
Reset filters

Settings
Now showing 1 - 10 of 11
Thumbnail Image
Publication

Analysis of WiFi Spatio-Temporal Data for Organic Fingerprinting-based Indoor Positioning System

2022-01-01 , Abdul Halim Ismail , Amirah Husna Mohd Hajazi , Muhamad Safwan Muhamad Azmi , Mohd Sani Mohamad Hashim , Mohd Nasir Ayob , Hassrizal Hassan Basri

The mobile robot navigation is the next huge topic after positioning utilizing fingerprinting-based Wireless Positioning System (WPS). Many of recent works does not discuss this topic yet since many open problems in positioning topic are not yet solved, for instance the issues on multi-devices heterogeneity, instability of WiFi signals, granularity problems in grid-based indoor environment and many others. However, we anticipate that both positioning and navigation works must run in parallel so that the succession are guaranteed. This paper describes the analysis of spatio-temporal data of the signal obtained from the WiFi Access Point. Initial results suggest that the difference between transmitter heights have an effect on the spatio-temporal data while the handover of maximum signal strengths is inherent when three WiFi APs are used.

View
Thumbnail Image
Publication

Effect of loading protocol on the mechanical properties of 316L stainless steel

2021-10-25 , Heng S.H. , Azmi M.S.M. , Mohd Afendi Rojan , Mohd Sani Mohamad Hashim , Mohd Nasir Ayob , Abdul Halim Ismail , Muhamad Saifuldin Abdul Manan , Abdullah S.

Two types of loading protocol, i.e., monotonic loading and cyclic loading, were compared to investigate the effect on the mechanical properties of 316L stainless steel. The specimen used is a dog-bone specimen in accordance with ASTM E8 and ASTM E606 standard. For cyclic loading, the multiple-step method is used to obtain the hysteresis loop of the material. A total of 13 strain amplitude conditions had been carried out, ranging from 0.05%-0.65%. The stress-strain curve shows that the cyclic stress-strain curve is higher than the monotonic stress-strain curve due to the cyclic hardening behaviour in the 316L stainless steel. The cyclic hardening behaviour increases the ultimate tensile stress of the material. However, when the material gains its strength through cyclic hardening, the ductility in the material will decrease.

View
Thumbnail Image
Publication

Numerical evaluation of aluminium 6026-T9 fracture toughness

2021-10-25 , Zulkifli A.N. , Muhamad Safwan Muhamad Azmi , Ishak Ibrahim , Mohd Sani Mohamad Hashim , Abdul Halim Ismail , Mohd Nasir Ayob

Fracture is the separation of an object into two or more pieces caused by crack growth under the action of applied stress. There are many different methods for fracture evaluation has been made but still lacks information on properties of Aluminium 6026-T9. Aluminium 6026 is non-toxic since it does not contain Tin (Sn) and features a great corrosion resistance. This study focuses on the mechanical properties and fracture toughness of Aluminium 6026-T9. The material is cut and shaped into dog-bone specimens by referring the ASTM E8 and was eventually undergoing a tensile test to evaluate the mechanical properties. A linear elastic analysis of three different crack characteristics which are single edge crack, double edge crack and center crack were performed in Mode I analysis to evaluate its fracture toughness. The stress intensity factor (SIF) value near the crack tip obtained from the simulation process were then compared with analytical value and had been discussed. The percentage of error found that the numerical and analytical values are closed to each other.

View
Thumbnail Image
Publication

The Characterization of J-Integral for Elastic-Plastic Crack Growth Evaluation using Finite Element Analysis

2021-01-01 , Heng S.H. , Muhamad Safwan Muhamad Azmi , Mohd Afendi Rojan , Mohd Sani Mohamad Hashim , Abdul Halim Ismail

J-integral is a fracture mechanic parameter that can be used to characterize elastic-plastic fracture mechanic (EPFM) behavior. The path independent characteristic in J-integral is proposed by Rice [1], and it is widely used in a lot of research. Another approach is the load-displacement approach, where the J-integral is calculated by the area under the load-displacement curve. However, the validity of the J-integral value by load-displacement approach is yet to be confirmed. This paper is aimed to investigate the effect of crack length ratio of CT specimen to J-integral value by two approaches: path-integral approach and load-displacement approach. Finite element analysis of compact tension (CT) model with crack length ratio a/W between 0.2 to 0.5 was carried out under displacement δ between 0.2 to 1.0 mm using ANSYS parametric design language (APDL). The J value by path integral approach, Jpath is compared to the value calculated from load-displacement approach, Jp-d. It was found that path independency occurs for J value evaluated from path integral approach. A correction factor needs to be introduced since the load-displacement approach cannot be used for shallow crack cases

View
Thumbnail Image
Publication

Robot Face and Its Integration to the Mobile Robot for Wireless Signal Collection in the Fingerprinting-Based Indoor Positioning System

2021-12-01 , Sarhan M.A.H. , Abdul Halim Ismail , Mohd Nasir Ayob , Hashim M.S.M. , Muhamad Safwan Muhamad Azmi , Hassrizal Hassan Basri , Siti Marhainis Othman , Muhammad Juhairi Aziz Safar

The wireless data collection for instance the Received Signal Strength (RSS) of the Wireless Fidelity (Wi-Fi) remained unfavourable in the Indoor Positioning System utilizing the signal fingerprinting approach. This is because the enormous sampling time and routines works making it tedious human labour. To alleviate this issue, we propose to use a robot for wireless data collection. The robot, named 'ICSiBOT' is a service robot with multiple purpose such as assisting human in daily lives, guest or hospitality robot and man others. This paper mainly describes the ICSiBOT robot face with speech recognition technology and the integration of the robot face to the motion controller. The experimental was conducted to see the correlation between the synthesized instructions from the speech in terms of distance need to be travelled i.e., the location for wireless signal collection and translate them into actual distance travelled. The results showed that the robot is able to travel to the specific distance as instructed to the robot face.

View
Thumbnail Image
Publication

Analysis of WiFi Spatio-Temporal Data for Organic Fingerprinting-based Indoor Positioning System

2022-01-01 , Abdul Halim Ismail , Hajazi A.H.M. , Muhamad Safwan Muhamad Azmi , Mohd Sani Mohamad Hashim , Mohd Nasir Ayob , Hassrizal Hassan Basri

The mobile robot navigation is the next huge topic after positioning utilizing fingerprinting-based Wireless Positioning System (WPS). Many of recent works does not discuss this topic yet since many open problems in positioning topic are not yet solved, for instance the issues on multi-devices heterogeneity, instability of WiFi signals, granularity problems in grid-based indoor environment and many others. However, we anticipate that both positioning and navigation works must run in parallel so that the succession are guaranteed. This paper describes the analysis of spatio-temporal data of the signal obtained from the WiFi Access Point. Initial results suggest that the difference between transmitter heights have an effect on the spatio-temporal data while the handover of maximum signal strengths is inherent when three WiFi APs are used.

View
Thumbnail Image
Publication

An Experimental Study of Deep Learning Approach for Indoor Positioning System Using WI-FI System

2021-01-01 , Sa’ahiry A.H.A. , Abdul Halim Ismail , Latifah Munirah Kamarudin , Ammar Zakaria , Nishizaki H.

Global navigation satellite system (GNNS) is known for its capability to detect the whereabouts of any desired target such as vehicles and places. However, there is some disadvantage of these technologies as it can only get a precise location outside of the building because as the signal goes to indoor building, the signal becomes weaker due to attenuation. The Wi-Fi systems are the best alternative to GNNS in an indoor environment since the architecture is massively deployed in many recent buildings. However, Wi-Fi also has its disadvantage where its signal is non-linear due to various factors such as multipath and signal blockage indoors thus limiting the system accuracy. In this paper, a deep learning approach with standalone Wi-Fi technologies will be used to have a precise indoor positioning by using the fingerprinting method. The overall result shows that the average distance error between actual and estimated location is 20-cm and the highest error is 62-cm in an experimental area of 180-cm and 120-cm in x and y axis. This shows that deep learning is a possible method to have accurate and precise indoor positioning.

View
Thumbnail Image
Publication

Effect of Sample Sizes in Fingerprinting Database for Wi-Fi System

2021-01-01 , Sa’ahiry A.H.A. , Abdul Halim Ismail , Muhammad Juhairi Aziz Safar , Latifah Munirah Kamarudin , Mohd Sani Mohamad Hashim , Muhamad Safwan Muhamad Azmi , Toyoura M.

Indoor positioning system has been an essential work to substitute the Global Positioning System (GPS). GPS utilizing Global Navigation Satellite Systems (GNSS) cannot provide an accurate positioning in the indoor due to the multipath effect and shadow fading. Fingerprinting method with Wi-Fi technology is a promising system to solve this issue. However, there are several problems with the fingerprinting method. The fingerprinting database collected has different sample sizes where the previous researcher does not indicate any standard for the sample size to be used. In this paper, the effect of the sample sizes in fingerprinting database for Wi-Fi technology has been discussed deeply. The statistical analyzation for different sample sizes has been analyzed. Furthermore, two methods which are K- Nearest Neighbor (KNN) and Deep Neural Network (DNN) are being used to examine the effect of the sample sizes in term of accuracy and distance error. The discussion in this paper will contribute to the better sample size selection depending on the method taken by the user. The result shows that sample sizes are an important metrics in developing the indoor positioning system as it effects the result of the location estimation.

View
Thumbnail Image
Publication

Design and Development of a Service Robot for Wi-Fi RSSI Fingerprint Data Collection

2020-09-18 , Bakri M.Q. , Abdul Halim Ismail , Mohd Sani Mohamad Hashim , Muhamad Safwan Muhamad Azmi , Muhammad Juhairi Aziz Safar , Marhaban M.H.

We have designed a service robot that can be used for Wi-Fi RSSI Fingerprint database construction for indoor positioning system. This work aims to aid and ease the signal fingerprint database construction process which currently conducted manually by carrying the data acquisition tools around the experimental field. The robot architecture design considered the values and constraint in performance, aesthetic, cost, and expandability. Analysis of the robot's mobile specification was made in order to choose the optimum hardware components. The robot has three main sections which are mobile platform, storage compartment, and user interactive screen that is capable to display facial expression and other useful information.

View
Thumbnail Image
Publication

Integrating Vision System to a Pick and Place Cartesian Robot

2021-12-01 , Tan K.S. , Mohd Nasir Ayob , Hassrizal Hassan Basri , Abdul Halim Ismail , Muhamad Safwan Muhamad Azmi , Mohd Sani Mohamad Hashim , Siti Marhainis Othman , Shahriman Abu Bakar , Low Y.H.

Vision aided pick and place cartesian robot is a combination of machine vision system and robotic system. They communicate with each other simultaneously to perform object sorting. In this project, machine vision algorithm for object sorting to solve the problem in failure sorting due to imperfection of images edges and different types of colours is proposed. The image is acquired by a camera and followed by image calibration. Pre-processing of image is performed through these methods, which are HSI colour space transformation, Gaussian filter for image filtering, Otsu's method for image binarization, and Canny edge detection. LabVIEW edge-based geometric matching is selected for template matching. After the vision application analysed the image, electrical signal will send to robotic arm for object sorting if the acquired image is matched with template image. The proposed machine vision algorithm has yielded an accurate template matching score from 800 to 1000 under different disturbances and conditions. This machine vision algorithm provides more customizable parameters for each methods yet improves the accuracy of template matching.

View