Finding a vacant parking space is becoming a real problem especially in areas with limited parking spots such as airports, shopping centres, offices, as well as universities. Searching for available parking slots is normally time consuming and always results in frustration especially when time is the major constraints. Moreover, vacant parking is hard to be noticed due to unsystematic parking system. This will result in longer searching time which can also lead to traffic congestion. In addition, lack of security enforcement on cars entering universities campus is also one of the main issues contributing to insufficient parking spaces. This might cause some unauthorized cars to take opportunity to get inside the campus without any approval and consent from security department. Therefore, A Cloud-based Automated Parking System for Smart Campus is developed in this project. It consists of a sub-system that is developed to display availability number of parking slots so that it will assist authorize users to easily find their parking spots. The proposed system can also recognize car plate number through Automated Car Plate Recognition (ACPR) mechanism which is located at the campus main entrance gate to avoid unauthorized cars from getting in. This has strengthened security level inside campus and ensure the safety of students and staffs. All the information collected are sent into the cloud and stored inside a database system. The information regarding vacant parking can also be displayed using the developed mobile apps.

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In wireless Network-on-Chip (WiNoC), radio frequency (RF) transceivers account for a significant power consumption, particularly its transmitter, out of its total communication energy. Current WiNoC architectures employ constant maximum transmitting power for communicating radio hubs regardless of physical location of the receiver radio hubs. This paper proposes a closed loop transmitting power control mechanism that, using bit error rate (BER) report obtained at receiver’s side, dynamically calibrates the transmitting power level needed for communication between the source and destination radio hubs to guarantee transmission reliability. Our proposed strategy achieves a significant total system energy reduction by about 40% with an average performance degradation of 3%.

Different types of image acquisition devices render different measure of colour depending on the specification of devices; even a same device will give different values of colours rendered, taking at certain duration of times. Most of the researches nowadays have attempted to solve these limitations and the researches of colour correction algorithm has been evolved recently. Colour correction algorithm has been widely used in various fields such as food industry, medical imaging, forensic cyber applications, film industries etc. In medical imaging, researchers have considered colour correction as an essential part in their pre-processing step prior to diagnosis. There are various statistical methods in colour correction and colour grading algorithm being implemented nowadays and finding the best algorithm with high accuracy is non-trivial. This paper presents comparative analyses of colour correction techniques that combine colour correction and colour grading algorithm using conventional gamma correction, polynomial regression, and proposed polynomial regression with modified gamma Look-up Table (pgLUT). It has been observed that our proposed pgLUT colour correction algorithm outperformed the conventional methods by 16.5%.