In the 21 st century, sensors have become common and part of everyday life. Such as touch-sensitive cell phones, computer monitors, elevator buttons, lamps that automatically dim or brighten, and even cars that park themselves. In addition, there are many applications of sensors that are hidden but control many facets of modern life such as in cars, airplanes, medical imaging, satellite communications and navigation. This research effort examines three sensor types, their data, and how to integrate it with a single microcontroller to accomplish simple tasks-dimming a light, sounding an alarm and showing a temperature rise. Three sensor types were used in this effort. First, an ultrasonic sensor was used to measure the distance from an object. A temperature sensor was used for monitoring temperature change from a human touch. Third, a Light Depending Resistor (LDR) sensor was used to detect different levels of light in a room. The goal of this research was to make a smart device that can be used to solve simple problems. Further applications could be applied to perform tasks such as controlling the temperature of a room or controlling the level of water in a meter. Also, robotics could be improved by providing information about distance to an object. Many applications can be enhanced based on this research.
The Quality of Service (QoS) is one of most important issues in providing an acceptable level of service. Communication engineers need a guide for action to improve QoS parameters such as data rate, bit error rate, latency, and jitter. Improving QoS includes a set of steps that should be performed by an engineer; these steps are belonging to two categories, system and network steps. In this paper we developed a flow chart of a general guide to improve QoS in a digital communication system, based on our knowledge of the modern communication system and impairments that lead to system degradation. We outline the options and advices to approach the subject of QoS in digital transmission.
1.INTRODUCTIONWireless Sensors Networks (WSNs) are widely considered as one of the interesting and rapidly developing fields. They have attracted great attention because of the diverse applications they support in both civilian and military sectors [1]. Typically, a WSN consists of a large number of low-cost, low-power, and multifunctional wireless sensor nodes with sensing, wireless communication and computation capabilities. In many applications, the sensor nodes are randomly deployed. Accordingly, the sensor nodes must organize themselves into a wireless network and cooperate to perform the required task. In addition, WSNs are usually battery powered which means it is very difficult to replace or recharge the batteries as soon as the nodes are deployed [2] [3]. Based on that, many techniques were proposed to achieve longer lifetime and efficient energy consumption. Clustering is one of the effective techniques used to save energy in WSNs [4].Clustering means organizing sensor nodes into different groups called clusters. In each cluster, sensor nodes can be either a Cluster Head (CH) or an ordinary member node. A CH is the group leader in each cluster. It collects sensed data from member nodes, aggregates, and transmits the aggregated data to the next CH or to the Base Station [5]. The role of an ordinary member node is to sense data from the environment in which they are deployed and send it to the corresponding CH.
The Bit Error Rate (BER) is a key parameter of the Quality of Service (QoS) for engineers and designers of digital communication systems and networks. At the present time, a set of models and methods are exist for calculating the BER. But these methods are complex and require large computing cost.In this paper, we provide a new model for calculating the BER. This model simplifies the procedures in the existing models and reduces the computing time. In the same time, the proposed model save the accuracy and the state consideration of existing models.
Now days, digital communication systems become complex and sophisticated. Not all vendors, if any, can understand the system and components of system that represent different modulation techniques, line and block coding, multiplexing and multiple access.They need the conclusion about which of modulation techniques is the suitable for transmission and in the same time can save the power and bandwidth.Engineers can study and analyze the modulation techniques and then compare between them to give such conclusion using modeling and simulation.MATLAB is a high level mathematical language for technical computing.In this paper we use MATLAB environment as simulation software to give on display a clear result that used to compare between two digital Passband modulation techniques BPSK and QPSK, and pinpoint the performance of the two techniques over selected parameters.
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