Mobile Ad-Hoc network (MANET) is a popular type of wireless network that is formed by a collection of mobile nodes. Each node in such a network has the capability to communicate with its neighbors and non-neighbors through a wireless medium without using any existing network infrastructure. Due to the lack of infrastructure, all nodes in Ad-Hoc network are designed to act as an end system and a router for other nodes. Traditionally, the dominant design methodology for network protocols was based on the open systems interconnection (OSI) reference model. This methodology divided the stack into seven layers in which each layer operates independently. Due to the dynamics of the Unmanned Aerial Vehicle (UAV) Ad-Hoc network, the conventional protocol stack is not sufficiently flexible to achieve certain quality of services (QoS) required by some applications. To overcome the limitations of the layering technique, cross-layering approach was implemented in this dissertation to adjust some key parameters in the first three layers of the OSI model based on the aircraft attitude variations (pitch, roll and yaw) and the variation of wireless links. To that respect, directional antennas were used by the UAVs to extend the coverage area and reduce the number of hops between the source and destination. Meanwhile, since the traditional Medium Access Control (MAC) protocol assumed the use of Omni-directional antennas, we designed a new MAC scheme that adapts its parameters based on the channel Bit-Error-Rate (BER) which is affected by the new antenna system and aircraft attitude. As for the routing protocol, we modified the Optimized Link State Routing (OLSR) protocol in such a way that the decision for selecting the route will be based on a local profile that holds the gathered information from the first three layers. UAV Ad-Hoc network was implemented by using a discrete event simulator called Optimized Network Engineering Tool (OPNET). We investigated the performance of the proposed techniques and compared them with the existing schemes. The simulation results showed that the proposed techniques improved the network performance and gave results better than the existing protocols in terms of throughput and End-to-End delay.
Unmanned aerial vehicles (UAVs) have the potential of creating an ad hoc communication network in the air. Most UAVs used in communication networks are equipped with wireless transceivers using omnidirectional antennas. In this paper, we consider a collection of UAVs that communicate through wireless links as a mobile ad-hoc network using directional antennas. The network design goal is to maximize the throughput and minimize the end-to-end delay. In this respect, we propose a new medium access control protocol for a network of UAVs with directional antennas. We analyze the communication channel between the UAVs and the effect of aircraft attitude on the network performance. Using the optimized network engineering tool (OPNET), we compare our protocol with the IEEE 802.11 protocol for omnidirectional antennas. The simulation results show performance improvement in end-to-end delay as well as throughput.
An EEG-based brain-computer system for automating home appliances is proposed in this study. Braincomputer interface (BCI) system provides direct pathway between human brain and external computing resources or external devices. The system translates thought into action without using muscles through a number of electrodes attached to the user's scalp. The BCI technology can be used by disabled people to improve their independence and maximize their capabilities at home. In this paper, a novel BCI system was developed to control home appliances from a dedicated Graphical User Interface (GUI). The system is structured with six units: EMOTIV EPOC headset, personal computer, Flyport module, quad band GSM/ GPRS communication module, LinkSprite JPEG Colour camera, and PIC-P40 board. EMOTIV EPOC headset detects and records neuronal electrical activities that reflect user's intent from different locations on the scalp. Those activities are then sent to the computer to extract specific signal features. Those features are then translated into commands to operate all appliances at home. The proposed system has been implemented, constructed, and tested. Experimental results demonstrates the feasibility of our proposed BCI system in controlling home appliances based on the user's physiological states. Abstract-An EEG-based brain-computer system for automating home appliances is proposed in this study. Braincomputer interface (BCI) system provides direct pathway between human brain and external computing resources or external devices. The system translates thought into action without using muscles through a number of electrodes attached to the user's scalp. The BCI technology
Abstract-Currently, blind people use a traditional cane as a tool for directing them when they move from one place to another. Although, the traditional cane is the most widespread means that is used today by the visually impaired people, it could not help them to detect dangers from all levels of obstacles. In this context, we propose a new intelligent system for guiding individuals who are blind or partially sighted. The system is used to enable blind people to move with the same ease and confidence as a sighted people. The system is linked with a GSM-GPS module to pin-point the location of the blind person and to establish a two way communication path in a wireless fashion. Moreover, it provides the direction information as well as information to avoid obstacles based on ultrasonic sensors. A beeper, an accelerometer sensor and vibrator are also added to the system. The whole system is designed to be small, light and is used in conjunction with the white cane. The results have shown that the blinds that used this system could move independently and safely.
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