Vehicular Ad Hoc Network (VANET) is a pillar of the envisioned Intelligent Transport System (ITS) and a subset of Mobile Ad Hoc Network that grants the communication in between the vehicles alongside with the absence of established communication infrastructure. Exposure to vulnerabilities of Vehicular Ad-Hoc Network (VANET) has been shown to be related to its nature of the environmental. For this reason, VANET security becomes a critical challenge that need to be resolved. In this paper, we assess the VANET security issues and discuss the challenges in VANET. Equally important, we comparatively review the security requirements, the type of attacks and capabilities of attackers present in VANET.

Abstract. This work introduces the design and development of smart green environment of garbage monitoring system by measuring the garbage level in real time and to alert the municipality where never the bin is full based on the types of garbage. The proposed system consisted the ultrasonic sensors which measure the garbage level, an ARM microcontroller which controls system operation whereas everything will be connected to ThingSpeak. This work demonstrates a system that allows the waste management to monitor based on the level of the garbage depth inside the dustbin. The system shows the status of different four types of garbage; domestic waste, paper, glass and plastic through LCD and ThingSpeak in a real time to store the data for future use and analysis, such as prediction of peak level of garbage bin fullness. It is expected that this system can create greener environment by monitoring and controlling the collection of garbage smartly through Internet-of-Things.

No abstract

No abstract

As one of the most important health monitoring systems, electrocardiography (ECG) is used to obtain information about the structure and functions of the human heart for detecting and preventing cardiovascular disease. Given its important role, it is vital that the ECG monitoring system provides relevant and accurate information about the heart. Over the years, numerous attempts were made to design and develop more effective ECG monitoring system. Nonetheless, the literature reveals not only several limitations in conventional ECG monitoring system but also emphasizes on the need to adopt new technology such as machine learning to improve the monitoring system as well as its medical applications. This paper reviews previous works on machine learning to explain its key features, capabilities as well as presents a general framework for improving ECG monitoring system.