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WiFi-enabled buses and stops may form the backbone of a metropolitan delay tolerant network, that exploits nearby communications, temporary storage at stops, and predictable bus mobility to deliver non-real time information. This paper studies the routing problem in such a network. Assuming the bus schedule is known, we maximize the delivery probability by a given deadline for each packet. Our approach takes the randomness into account, which stems from road traffic conditions, passengers boarding and alighting, and other factors that affect the bus mobility. In this sense, this paper is one of the first to tackle quasi-deterministic mobility scenarios. We propose a simple stochastic model for bus arrivals at stops, supported by a study of real-life traces collected in a large urban network. A succinct graph representation of this model allows us to devise an optimal (under our model) single-copy routing algorithm and then extend it to cases where several copies of the same data are permitted. Through an extensive simulation study, we compare the optimal routing algorithm with three other approaches: minimizing the expected traversal time over our graph, maximizing the delivery probability over an infinite time-horizon, and a recently proposed heuristic based on bus frequencies. We show that our optimal algorithm shows the best performance, but it essentially reduces to minimizing the expected traversal time. When transmissions fail frequently (more than half of the times), the algorithm behaves similarly to a heuristic that maximizes the delivery probability over an infinite time-horizon. For reliable transmissions and values of deadlines close to the expected delivery time, the multi-copy extension requires only 10 copies to almost reach the performance of the costly flooding approach. I. INTRODUCTION We consider an opportunistic data network formed by (some) buses and bus stops in a town equipped with wireless devices, e.g. based on WiFi technologies, like in DieselNet [1]. Most of the stops act as disconnected relay nodes (the throwboxes in [2]), and a few of them are also connected to the Internet. Data are delivered across the town following the store-carry-forward network paradigm [3], based on multihop communication in which two nodes may exchange data

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WiFi-enabled buses and stops may form the backbone of a metropolitan delay tolerant network, that exploits nearby communications, temporary storage at stops, and predictable bus mobility to deliver non-real time information. This paper studies the routing problem in such a network. Assuming the bus schedule is known, we maximize the delivery probability by a given deadline for each packet. Our approach takes the randomness into account, which stems from road traffic conditions, passengers boarding and alighting, and other factors that affect the bus mobility. In this sense, this paper is one of the first to tackle quasi-deterministic mobility scenarios. We propose a simple stochastic model for bus arrivals at stops, supported by a study of real-life traces collected in a large urban network. A succinct graph representation of this model allows us to devise an optimal (under our model) single-copy routing algorithm and then extend it to cases where several copies of the same data are permitted. Through an extensive simulation study, we compare the optimal routing algorithm with three other approaches: minimizing the expected traversal time over our graph, maximizing the delivery probability over an infinite time-horizon, and a recently proposed heuristic based on bus frequencies. We show that our optimal algorithm shows the best performance, but it essentially reduces to minimizing the expected traversal time. When transmissions fail frequently (more than half of the times), the algorithm behaves similarly to a heuristic that maximizes the delivery probability over an infinite time-horizon. For reliable transmissions and values of deadlines close to the expected delivery time, the multi-copy extension requires only 10 copies to almost reach the performance of the costly flooding approach. I. INTRODUCTION We consider an opportunistic data network formed by (some) buses and bus stops in a town equipped with wireless devices, e.g. based on WiFi technologies, like in DieselNet [1]. Most of the stops act as disconnected relay nodes (the throwboxes in [2]), and a few of them are also connected to the Internet. Data are delivered across the town following the store-carry-forward network paradigm [3], based on multihop communication in which two nodes may exchange data

Nowadays, the evolution in transportation technologies makes the necessity for increasing road safety. In this context, we propose the implementation of a smart onboard GPS/GPRS system to be attached to vehicles for monitoring and controlling their speed. In case of traffic speed violation, a GPRS message containing information about the vehicle such as location and maximum speed is sent to a hosting server located in an authorized office so that the violated vehicle is ticketed. Moreover, this system can also track the vehicle's current location on a Google Map, which is mostly beneficial when vehicles should follow a specific road and in case of robbery. Also geo-casting can have a major role in this model. Some sensors, such as shock/vibration sensor usually attached to the air-bags in vehicles, are attached to the system that in case of accident, it will send notifications to the nearest hospital, police station and civil defense. Our proposed model can be utilized for different implementations, both in public and private sectors. While similar existing systems in Palestine have focalized just on the tracking aspect of vehicles' monitoring, it would be the first system supporting both ticketing and tracking.

Recently, remote monitoring systems have evolved to respond for particular needs in healthcare sector, which is an essential pillar in the modern concept of smart city, we propose a smart system to monitor patient current health conditions, as a smart healthcare system based on the widely spread available technologies; namely, GSM and GPS. Statistics shows that hypertensive heart disease and blood pressure are risk factors for high death rate to decrease it a preventive measures should be applied providing a real-time health monitoring system, to save patients life at acceptable time. The objectives of this paper is to provide an effective system model, that will track, trace, and monitor patient vital readings in order to provide efficient medical services in time. By using sensors, the data will be captured and compared with a predefined threshold. The study focuses on heartbeat rate, and body temperature, thus in case of emergency an SMS will be sent to the Doctors mobile containing measured values and position. Moreover, the paper demonstrates the possibility of building a complete end-to-end smart healthcare monitoring system by using wide range of available sensors for more vital human health parameters to connect patient with doctors in cases of emergency.