Phak Len Al Eh Kan
Thumbnail Image
Preferred name
Phak Len Al Eh Kan
Official Name
Phak, Len Al Eh Kan
Alternative Name
Ehkan, Phaklen
Kan, P. L.Eh
Ehkan, Phak Len
Ehkan, P. L.
Eh Kan, P.
Eh Kan, P.
Al Eh Kan, Phak Len
Eh Kan, Phaklen
Kan, P. Eh
Main Affiliation
Scopus Author ID
37005452000

Research Output

Filters

3
Reset filters

Settings
Now showing 1 - 3 of 3
Thumbnail Image
Publication

Automatic vehicle identification system using number plate recognition in POLIMAS

2020-03-20 , Keraf N.D. , Phak Len Al Eh Kan , Kelian V.H. , Noor N.M. , Darus H. , Loke E.

The security and management of transportation system becomes an important key in controlled place such as campus area. With an increased number of vehicles, there is a need for vehicle identification mechanism that is effective, affordable and efficient. This paper presents the development of automatic vehicle identification system using NP recognition in POLIMAS. Number Plate (NP) Recognition is an image processing technology in computer vision which captures the image of the vehicle and recognizes its NP. The system is installed at the main entrance to ensure that only the authorized vehicles can enter the campus area. Once the vehicle is detected by the input sensors, a system will capture the image of vehicle plate number. An image is then extracted and investigated character segmentation by using optical character recognition. The method used for detection of a plate number is by pre-processing of the image and using a combination of Sobel Edge Detection and Laplacian Edge Detection Techniques. Bounding Box technique is used to find the NP and character recognition. The accuracy of NP recognition has an average of 87%. The system is sustainable as the camera will only be switched on when a vehicle is present.

View
Thumbnail Image
Publication

Toward Adaptive and Scalable Topology in Distributed SDN Controller

2023-03-01 , Kelian V.H. , Mohd Nazri Mohd Warip , R Badlishah Ahmad , Phak Len Al Eh Kan , Fazrul Faiz Zakaria , Mohd Zaizu Ilyas

The increasing need for automated networking platforms like the Internet of Things, as well as network services like cloud computing, big data applications, wireless networks, mobile Internet, and virtualization, has driven existing networks to their limitations. Software-defined network (SDN) is a new modern programmable network architectural technology that allows network administrators to control the entire network consistently and logically centralized in software-based controllers and network devices become just simple packet forwarding devices. The controller that is the network's brain, is mostly based on the OpenFlow protocol and has distinct characteristics that vary depending on the programming language. Its function is to control network traffic and increase network resource efficiency. Therefore, selecting the right controllers and monitoring their performance to increase resource usage and enhance network performance metrics is required. For network performance metrics analysis, the study proposes an implementation of SDN architecture utilizing an open-source OpenDaylight (ODL) distributed SDN controller. The proposed work evaluates the deployment of distributed SDN controller performance on three distinct customized network topologies based on SDN architecture for node-to-node performance metrics such as delay, throughput, packet loss, and bandwidth use. The experiments are conducted using the Mininet emulation tool. Wireshark is used to collect and analyse packets in real-time. The results obtained from the comparison of networks are presented to provide useful guidelines for SDN research and deployment initiatives.

View
Thumbnail Image
Publication

A Proposal of Low Cost Home Automation System Using IoT and Voice Recognition

2020-03-20 , Phak Len Al Eh Kan , Keraf N.D. , Kelian V.H. , Fazrul Faiz Zakaria , Bei, Sin Zhen

Home Automation System is becoming more popular day by day due to its numerous benefits. This project proposes an idea in the design of low cost home automation system by using the Internet of Things (IoT) and voice recognition. The layout of the home divided into four areas and each area has own function and system. The Raspberry Pi 3 (RPi) Model B+ used as the main controller for the processing and transmitting the input data. IoT provided huge storage for data collection from sensors and home appliances. An Android application is developed to monitor the home environment and remotely control the home devices by using the button or voice. The speaker-independent recognition system by using Google Voice to Text on Android embedded in this project for physically challenged people to control the electrical appliances without moving. All the data will be stored in Firebase and can be retrieved at any time by the application and the RPi board. There is a side view of a prototype model with two floors and divided into four home areas. This Low-Cost Home Automation System using IoT and Voice Recognition is successfully achieved the project's objective.

View