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Wireless sensor networks and their logistics implementations

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In the paper the Wireless Sensor Networks, their operations frameworks, architecture and topologies are presented. An attention is focused on programmable Web service applicability of these sensor networks in implementations referred to two programming levels: low programming level of data sensors and high language programming level in distributed structures addressed to dedicated application. Wireless Sensor Network Systems implementations are illustrated in logistics implementation.
INTRODUCTION
Wireless Sensor Networks (WSN) are developed as specified area of wireless computing networks general purposes. They make distributed systems, usually composed of embedded devices, each equipped with processing unit, wireless communication interface and a number of sensors or actuators. The implementation of such networks is determined by type of sensors and type of implementations, hardware requirements and programming methods used. So, such sensor network can cover the wide area of implementations from satellite imaging systems, through various purposes measuring systems: seismic, thermal, acoustic..., spatial environment or meteorological monitoring to air quality stations, and security cameras. For growing WSN applications, recently, the special attention is paid to support the WSN services by programming methods and aided using the Web integrating the communication and coordination of the data among the WSN nodes and the trunk lines [1-3].
The transport is one of possible application the Wireless Sensor Networks, mainly, in the area of intelligent road systems and logistics where mobile and wireless communication technology allow in real-time to manage the global interconnections [4-6]. In these systems to process the information coming from many different data sources the SQL (Structure Query
Language) stream computing platform usually is implemented. The SQL-stream solution reduces the time and cost to deploy sensor network systems aided by the databases to process large data streams. In these systems any number of data sources can be connected in real-time, mainly, using middleware approach making a standard of scalable sensor network applications. Such sensor application examples can be the Intelligent Transportation systems improving road safety, optimize transportation efficiency, reduce pollution, and providing data to support the national security issues [7-8]. (...)

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