Department Publications

This paper presents modelling, simulation and implementation of a quadrotor Unmanned Ariel Vehicle (UAV) Focus of this work is to gain in-depth understanding of quadrotor dynamics to develop a simulator and a laboratory platform to facilitate future development of control algorithms, automatic navigation systems, and trajectory planning for quadrotors. Quadrotor dynamics is modeled using Newton-Euler method. The model predicts the effects of the forces and torques generated by the four propellers on the quadrotor motion. Based on the model, a quadrotor simulator was developed in MATLAB® Simulink, on which various control algorithms can be developed and tested. A quadrotor prototype was built on which some of the control algorithms were tested experimentally in different environments to evaluate the stability and controllability of the platform. Experimental flight data and simulation results were …

quadrotor microaerial vehicles (MAVs) are simple robotic platforms with regard to their construction. In their basic form, they are no more than two counterrotating propeller pairs attached symmetrically to a rigid crosslike frame, along with the means to control the speed of each individual propeller. This symmetric design has enabled the quadrotor to become a simple but powerful vertical takeoff and landing aerial platform popular among the robotics community.

Congestion in a networked control system (NCS) has many undesirable effects that can make a control system unstable if severe enough. These include delays and packet drops. Therefore, reducing network traffic, including traffic generated by the NCS itself is a necessity. In event based control (EBC) a control signal is generated when a specific event is triggered such as the control error exceeding a predetermined threshold. When the rate of change of a variable is bounded, event triggering reduces the effective frequency in which control signals have to be generated when compared to a system with periodic sampling. This paper proposes a new method of event triggering called event triggered adaptive differential modulation (ETADM) that combines the bandwidth reduction strategies of event triggering and human speech coding techniques. The proposed method can be applied to nonlinear systems with a …

An informative digital map is a prerequisite for future Intelligent Transportation System (ITS) applications such as lane level navigation systems. Preparing and updating such detailed digital maps by using existing methods such as surveying and image digitization is not practical due to the time and cost involved. We propose a method that statistically mines Global Positioning System (GPS) trajectory data obtained from vehicles to generate a lane level digital map of the road. The proposed method is capable of generating a digital map of the road which contains lane centerlines. The proposed method is independent of the lane width, lane parallelism and can handle lane splits and merges. In addition, a method that can be used to generate a map of lane boundaries is also presented. The proposed methods have been tested using the GPS data collected using vehicles equipped with GPS enabled mobile phones …

The outage probability of a multiuser two-hop amplify-and-forward relaying system employing opportunistic scheduling is investigated. A practically important case where there are cochannel interference signals present at the network is considered for the analysis. Exact expressions and closed-form lower bounds are derived for the outage probability. Exact closed-form expressions are derived for the system outage probability when interference signals are present at the relay and at the destination separately. A closed-form lower bound is derived for the outage probability when the relay and the destination nodes are affected by interference simultaneously. The effects of channel state information feedback delay are investigated for special cases. In addition, asymptotic outage probability results are derived to obtain useful insights on the effects of interference and feedback delay. The novel expressions can be …

This paper studies the structure of downlink sum-rate maximizing selective decentralized feedback policies for opportunistic beamforming under finite feedback constraints on the average number of mobile users feeding back. First, it is shown that any sum-rate maximizing selective decentralized feedback policy must be a threshold feedback policy. This result holds for all fading channel models with continuous distribution functions. Second, the resulting optimum threshold selection problem is analyzed in detail. This is a nonconvex optimization problem over finite-dimensional Euclidean spaces. By utilizing the theory of majorization, an underlying Schur-concave structure in the sum-rate function is identified, and the sufficient conditions for the optimality of homogenous threshold feedback policies are obtained. Applications of these results are illustrated for well-known fading channel models such as Rayleigh …

Typical Automatic Number Plate Recognition (ANPR) system uses high resolution cameras to acquire good quality images of the vehicles passing through. In these images, license plates are localized, characters are segmented, and recognized to determine the identity of the vehicles. However, the steps in this workflow will fail to produce expected results in low resolution images and in a less constrained environment. Thus in this work, several improvements are made to this ANPR workflow by incorporating intelligent heuristics, image processing techniques and domain knowledge to build an ANPR system that is capable of identifying vehicles even in low resolution video frames. Main advantages of our system are that it is able to operate in real-time, does not rely on special hardware, and not constrained by environmental conditions. Low quality surveillance video data acquired from a toll system is used to …

Brain-Computer Interaction (BCI) is a technology developed with the purpose of building a pathway between the brain and computer which is independent of neuromuscular functions. Potential applications in rehabilitation of patients with motor disabilities and video gaming make BCI an important field of research. A task like controlling a prosthetic limb using BCI is challenging. Performing this with readily available consumer grade EEG devices complicates the matters further due to lower accuracies. This paper presents the work related to an online classifier for imagined hand movement implemented using Emotiv Epoc for EEG data capturing. The system attempts to discriminate between left and right hand movement imagination by analysing the recordings of two electrodes placed over the motor-cortex. Auto-Regression (AR) based signal processing techniques are employed to derive features that enable …

A low-complexity multirate 3-D spatio-temporal FIR cone and frustum filter structure is proposed having potential applications as a spatio-temporal directional filter. The cone filter structure employs a 1-D modified discrete Fourier transform (DFT) filter bank and 2-D spatial filters. The frustum filter having a double-frustum-shaped passband oriented along the temporal frequency axis is approximated by employing an appropriate subset of subbands. Low computational complexity is achieved by maximal decimation in the temporal dimension, and by employing the DFT-polyphase realization to implement the 1-D modified DFT filter bank. The cone and frustum filters are almost alias free, and provide near-perfect reconstruction. The reduction in computational complexity, relative to undecimated and under-decimated realizations, is numerically confirmed by means of a potential application involving the attenuation of …

A wired fence based intrusion detection and alerting mechanism for boundaries separating wildlife habitats and human settlements was implemented, particularly as a solution to the Human-Elephant Conflict (HEC). The objective of the research reported in this paper is to propose and verify an alternative technique for this wired fence based alerting mechanism to overcome its limitations and to improve its effectiveness. This article presents a comprehensive study of alternative solutions with deliberate consideration of the practical constraints. Wi-Alert is a wireless sensor network based intrusion detection system proposed as the best alternative solution. This article reports the outcomes of the first two phases of ongoing developments of Wi-Alert. The first phase of experiments was conducted to investigate the multi-path effect reduction techniques at one site. In the next phase, experiments were conducted to verify …

Opportunistic beamforming is a reduced feedback communication strategy for vector broadcast channels which requires partial channel state information (CSI) at the base station for its operation. Although reducing feedback, this strategy in its plain implementations displays a linear growth in the feedback load with the total number of users in the system n, which is an onerous requirement for large systems. This paper focuses on a more stringent but realistic O(1) feedback constraint on the feedback load. Starting with a set of statistically identical users, we obtain the tradeoff curve tracing the Pareto optimal boundary between feasible and infeasible feedback-capacity pairs for opportunistic beamforming. Any point on this tradeoff curve can be obtained by means of homogeneous decentralized threshold feedback policies, which are rate-wise optimal, in which a user feeds back only if the received signal quality is …

Listening to the heart sounds is a common practice in identifying cardiac malfunctions. Since this method has many limitations, tools that aid physicians in their diagnosis of heart diseases are very useful. This paper presents a software tool to predict cardiac abnormalities which can be identified using heart sounds. Both heart sound information and symptoms are used in disease prediction. First audio inputs at four clinically important locations on the chest are acquired using an electronic stethoscope and entered to a database with symptoms for each patient. After de-noising, prominent features and statistical parameters needed for disease detection are extracted from the heart sound samples using several algorithms. Then the disease classification is performed to find out possible disease and murmur types. The software tool reported in this paper is capable of identifying normal heart sounds and abnormal heart …

Wireless Sensor Networks consist of inexpensive, low power sensor nodes deployed to monitor the environment and collect data. Gathering information in an energy efficient manner is a critical aspect to prolong the network lifetime. Clustering algorithms have an advantage of enhancing the network lifetime. Current clustering algorithms usually focus on global re-clustering and local re-clustering separately. This article, proposed a combination of those two re-clustering methods to reduce the energy consumption of the network. Furthermore, the proposed algorithm can apply to homogeneous as well as heterogeneous wireless sensor networks. In addition, the cluster head rotation happens, only when its energy drops below a dynamic threshold value computed by the algorithm. The simulation result shows that, the proposed algorithm prolong the network lifetime compared to existing algorithms.

The paper presents a wireless body area sensor network (BASN) for evaluating the effectiveness of fitness exercising. The goal of our work is to provide a mobile and an accurate way of quantifying the energy expenditure during a fitness exercise session. While energy expenditure estimates are available in modern exercise machines, no accurate method exists for outdoor exercising. The prototype system implemented includes an IEEE 802.15.4(Zigbee) based wireless body area sensor network which measures physiological and kinetic features related to the activity being monitored, and a mobile application for visualization of the estimated energy expenditure. The paper outlines the sensor hardware used, the body area network which collects the measurements from the sensor nodes, the algorithm for energy computation and experimental results. The system, once trained can be used with any form of outdoor …

The natural sciences have been transformed with the incorporation of advanced technologies, and the current technological wave of change is also revolutionizing biological science. With the wide use of herbal medicines in traditional medical systems, the demand for medicinal plants has increased enormously. Though the current trend has made the use of medicinal plants more popular, we still require better methods to distinguish between medicinal plants and plants which do not possess medicinal value. Manual methods of plant recognition rely on a plants flower information. However, these manual processes of flower recognition are not straightforward for lay persons unless expert guidance is provided. Motivated by this reasoning, an intelligent flower analyzing system has been developed to recognize medicinal plants. Various tests have been performed on 160 images taken from four types of flowers, to recognize flowers based on their colour and shape features. The experiment was carried out using Support Vector Machine (SVM) and Principal Component Analysis (PCA) methodologies respectively for colour and shape extraction. Acquiring an average of 65% recognition rate implies that the applicability PCA and SVM in the specified domain is a valuable step forward.

We present a novel method where smart phone sensors are used to sense the prevailing traffic situation and to share extracted information among a community. Instead of using the power-hungry GPS receiver in the mobile device for detecting congestion through vehicular motion, we use the accelerometer along with a novel algorithm. We show that traffic congestion situations can be identified with 78% accuracy with our technique. Vehicular traffic has become a severe problem, particularly in the less developed countries. Therefore pre awareness of congestion situations is very important for an efficient lifestyle.

Grouping the detected feature points traditionally requires the storage of long corner tracks. The traditional method does not permit to arrive at a decision to cluster the feature points based on a frame by frame basis. This paper presents a method to group the feature points directly into objects using the most recent 20 frames. The detected corner features are validated and clustered based on two approaches. When objects move in isolation, an EM algorithm is used to cluster and every object is detected and tracked. When objects move under partial occlusion, the corner features are clustered based on an agglomerative hierarchical clustering approach. A probabilistic framework has also been applied to determine the object level membership of the candidate corner features. A novel foreground estimation algorithm with an accuracy of 98% based on color information, background subtraction result and detected …

Wireless sensor networks (WSNs) composed of large numbers of sensor nodes to monitor the environment and collect data. Self-organization of sensor nodes has been widely investigated to enhance the quality of service provided by WSNs. This paper proposes a Severity based Clustering Algorithm for Emergency (SCAE) for WSNs. The residual energy of nodes and severity of the emergency environment are the key parameters of SCAE. The severity of the emergency situation is estimated by using Dempster-Shafer theory. SCAE minimizes the communication loss due to node failures in an emergency environment. This is achieved by delaying the cluster head failures in the network and allocating less priority to non-cluster heads to select their cluster head which might get dropped from the network quickly. Communication failures due to node failures have been minimized successfully by considering the severity …

Wireless sensor networks may contain hundreds or thousands number of sensor nodes, monitoring specified parameters in the environment. These sensor nodes have the ability to communicate with each other or directly to an external base station. Current clustering algorithms provide an effective way to prolong the network lifetime. However, gathering information and communicating with each other is crucial in an emergency situation. To address this problem, the paper proposes an emergency response unequal clustering algorithm for wireless sensor networks. The proposed algorithm has been able to utilize the energy usage of the network with the novel approach in unequal clustering. Furthermore, this addresses the node failures in an emergency situation. The simulation result shows that the proposed algorithm has optimized the energy usage and reduce the communication failure compared to other …

The performance of a random vector quantization based transmit precoding distributed antenna system is investigated in terms of the achievable ergodic rate. An approximate expression is derived for the ergodic rate of the system considering the effects of path loss, Rayleigh fading and out-of-cell interference. A moment matching technique is used to approximate the desired signal power and the total interference power distributions of the system using a Gamma distribution. The proposed approximation estimates the performance of the system accurately and saves computational time in simulations.

In an emergency, combining Wireless Sensor Network's data with the knowledge gathered from various other information sources and navigation algorithms, could help safely guide people to a building exit while avoiding the risky areas. This article presents an emergency response and navigation support architecture for data gathering, knowledge manipulation, and navigational support in an emergency situation. At normal state, the system monitors the environment. When an emergency event detects, the system sends messages to first responders and immediately identifies the risky areas from safe areas to establishing escape paths. The main functionalities of the system include, gathering data from a wireless sensor network, which is deployed in a multi-story indoor environment, processing it with information available in a knowledge base, and sharing the decisions made, with first responders and people in …

This paper analyses the FIFO design for the receiver of 10GBase-X PCS sublayers specified by IEEE 802.3 CSMA/CD Standards. The proposed FIFO design will save the gate count, power and the silicon area in ASIC design considerably.

For the development in the agricultural sector in Sri Lanka, it is a well accepted fact that technology should be introduced to the field of agriculture. Here Electronic Engineers can play a major role. As the first step of this process the multi-disciplinary module Agricultural Electronics was formed and introduced to the undergraduates of the specialized field Electronic and Telecommunication. The necessity, content and the outcomes of the module were demonstrated in this paper as a new trend in Engineering Education; therefore any nation would be able to adopt this multi-disciplinary approach for the benefit of their country.

A wireless sensor network (WSN) specifically designed for detecting elephant intrusions into villages that border wildlife reserves and alerting threatened communities of the location of the same is described. Novel strategies for hardware, firmware and communication have been applied, exploiting the rareness of events to be detected and the low data rates and light traffic load involved, in order to balance power consumption, cost, easy installation and testing in rural areas. Attempts have been made to build in automatic preventive maintenance measures and maintainable by personnel without technical know-how. The paper presents the design of the system and the experimental evaluation of a prototype implementation.

Multi field packet classification is the enabling function for many novel and emerging network applications. Exponential growth of Internet traffic and classification rule sets demand novel hardware based architectural approaches to packet classification. Even though this is an immensely studied area, packet classification that supports scalability in both line rates and rule sets is scarce. In this paper we present experience gained while implementing a parallel packet classification engine architecture on a popular reconfigurable router platform. The architecture exploits parallelism offered in modern hardware technologies to classify multiple packets simultaneously to increase the throughput. The architecture is also capable of utilizing temporal locality present in internet traffic to increase the throughput. The Architecture was implemented on NetFPGA platform and packet classification was done at full line rate without …