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Wireless network sensors and their use in traffic monitoring, traffic density determination or vehicle speed detection and classification have recently been the focus of interest for researchers. This article describes how a new sensor circuit was designed to deliver instantaneous, real-time and novel solutions as a vehicle detection system, which is more powerful than the nodes used in other studies, and gives results with smaller error margins due to its serial communication qualification. With the proposed logic algorithm, it was possible to categorise the instantaneous traffic status of a road in four levels: no traffic, mild traffic, heavy traffic and very heavy traffic. Additionally, with the nodes placed at the beginning and the end of the road, the number of vehicles per hour for a day was determined and traffic was analysed. Then, vehicles passing by were classified with a proposed classification algorithm and magnetic signature length (MSL) parameter as cars, minibuses, buses and trucks, and an accuracy rate of 95% was obtained. As the last application, the direction of motion of the vehicle on the x-axis as well as left-to-right or right-to-left directions was determined, and the result was 94% accurate. The simplicity of the proposed algorithms, the absence of any complex mathematical calculations, the low cost of the sensor node and circuit and the low power consumption of the communication system demonstrate the superiority of this system in comparison with other studies. [ABSTRACT FROM AUTHOR]

Route planning and recommendation have received significant attention in recent years. In this light, we study a novel problem of planning unobstructed paths in traffic-aware spatial networks (TAUP queries) to avoid potential traffic congestions. We propose two probabilistic TAUP queries: (1) a time-threshold query like 'what is the path from the check-in desk to the flight SK 1217 with the minimum congestion probability to take at most 45 minutes?', and (2) a probability-threshold query like 'what is the fastest path from the check-in desk to the flight SK 1217 whose congestion probability is less than 20 %?'. These queries are mainly motivated by indoor space applications, but are also applicable in outdoor spaces. We believe that these queries are useful in some popular applications, such as planning unobstructed paths for VIP bags in airports and planning convenient routes for travelers. The TAUP queries are challenged by two difficulties: (1) how to model the traffic awareness in spatial networks practically, and (2) how to compute the TAUP queries efficiently under different query settings. To overcome these challenges, we construct a traffic-aware spatial network G( V, E) by analyzing uncertain trajectories of moving objects. Based on G( V, E), two efficient algorithms are developed to compute the TAUP queries. The performances of TAUP queries are verified by extensive experiments on real and synthetic spatial data. [ABSTRACT FROM AUTHOR]

ÀRouting protocols can decide for data packets which route is reachable and co-optimal, and may cause data packets to swarm into certain links, thus causing congestion on those links. General traffic engineering (GTE) technology provides ER-LSP/CR-LSP in MPLS networks to avoid this kind of congestion. However, GTE takes only the current data flow into account and establishes an ER-LSP/CR-LSP for this current data flow in order to guarantee QoS. Although this could resolve the issue raised by routing protocols, it may also waste some resource. In this article we focus on optimization of traffic engineering and propose an automatic traffic balance algorithm based on GTE technology. [ABSTRACT FROM AUTHOR]