This paper introduces a novel algorithm that increases the efficiency of the current cloud-based smart-parking system and develops a network architecture based on the Internet-of-Things technology. This paper proposed a system that helps users automatically find a free parking space at the least cost based on new performance metrics to calculate the user parking cost by considering the distance and the total number of free places in each car park. This cost will be used to offer a solution of finding an available parking space upon a request by the user and a solution of suggesting a new car park if the current car park is full. The simulation results show that the algorithm helps improve the probability of successful parking and minimizes the user waiting time. We also successfully implemented the proposed system in the real world.INDEX TERMS Smart-parking system, performance metrics.
Existing intelligent transport systems (ITS) do not fully consider and resolve accuracy, instantaneity, and compatibility challenges while resolving traffic congestion in Internet of Vehicles (IoV) environments. This paper proposes a traffic congestion monitoring system, which includes data collection, segmented structure establishment, traffic-flow modelling, local segment traffic congestion prediction, and origin-destination traffic congestion service for drivers. Macroscopic model-based traffic-flow factors were formalized on the basis of the analysis results. Fuzzy rules-based local segment traffic congestion prediction was performed to determine the traffic congestion state. To enhance prediction efficiency, this paper presents a verification process for minimizing false predictions which is based on the Rankine-Hugoniot condition and an origin-destination traffic congestion service is also provided. To verify the feasibility of the proposed system, a prototype was implemented. The experimental results demonstrate that the proposed scheme can effectively monitor traffic congestion in terms of accuracy and system response time.
Aquaculture is facing many challenges related to diseases and environmental pollution. Environmental and disease monitoring in aquaculture is to help authorities in planning and management, and to provide technical measures to support farmers. The study was carried out from January to October 2020, including 13 sites of supply water of brackish water shrimp farming areas of Nam Dinh, Nghe An, Ha Tinh, Quang Binh, Quang Tri, and Thua Thien Hue; 11 sites of clam/mollusc farming areas of Thai Binh, Thanh Hoa, and Quang Ninh; 11 sites of cage aquaculture of Hoa Binh, Yen Bai, and Hai Duong, with 23 monitoring times of the inlet water for brackish shrimp, 7 monitoring times for tilapia and freshwater cage culture. Alkalinity, ammonia, nitrite, total Vibrio, and VpAHPND values in shrimp farming water were higher than Vietnam’s environmental standard, valued at 12.37, 25.08, 16.67, 3.68, and 0.67% respectively. Salinity, ammonia, nitrite values, and total Vibrio in the mollusc farming water were higher than Vietnam’s environmental standard, which were 23.38, 33.77, 32.50, and 3.9%, respectively. Chemical oxygen demand and nitrite in the tilapia and freshwater cage farming water were higher than Vietnam’s environmental standard, which were 29.87 and 22.08%, respectively. Timely recommendations and warnings helped farmers minimise the damage caused by environmental pollution and diseases.
Wavelength Division Multiplexing (WDM) has been widely applied in optical adddrop multiplexing (OADM) fiber metro systems with an increasing number of wavelength channels and sufficiently narrow channel spacing. The problem that appears here is the signal distortion produced by dispersion and nonlinearity effects. To cope with these effects, many compensation solutions have been introduced, such as digital compensation (DC) solutions on technology of digital signal processing (DSP) or optical phase conjugation (OPC) on alloptical domain. In fact, research on using OPC to compensate for dispersion and nonlinearity in metro transmission systems are incomplete, especially with large number multiplexing systems. In this paper, we propose to use OPC for dispersion and nonlinear compensation in DWDM metro systems. Specifically, we focus on two common types of modulation signals: QPSK and 16-QAM; operations in 16- and 32-channel dense WDM system. The simulation results show that the system quality increases significantly when using OPC to compensate for dispersion and nonlinearity, e.g. when transmitting 16-QAM signals in a 32-channel system passing through 20 add/drop nodes, the gain of Q factor is greater than 2 dB.
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