Electrical and Electronic Engineering - Research Publications
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ItemNo Preview AvailableEvolution of Short-Range Optical Wireless Communications(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023-02-15)
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ItemIntelligent Radio Resource Allocation for Human-Robot Collaboration(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022)
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ItemNon-Protruding Hazard Detection for the Aged Vision-Impaired(IEEE, 2016)Usage of the traditional white cane by the elderly with vision impairment is inefficient as many are also reliant on ambulatory aids such as wheelchairs and walking frames. The fall occurrence when using ambulatory aids is higher, contributed by non-protruding hazards such as potholes and drop-offs. Currently available technology for blind navigation, predominantly based on proximity sensing, is not designed to detect non protruding hazards. We address this critical need by developing a new optical laser system that combines innovative approaches in optical laser projection, vision-sensing, pattern recognition, and machine learning. Here, we present an overview of the system, including a new feature descriptor termed Histogram of Intersections, and results from our proof-of-concept demonstration.
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ItemA vision-based system to detect potholes and uneven surfaces for assisting blind people(IEEE, 2016)Vision is one of the most advanced and important sensory input in humans. However, many people have vision problems due to birth defects, uncorrected errors, work nature, accidents, and aging. The white cane and guide dog are the most widely used means of navigation for the vision-impaired. With advancements in technology, electronic devices have been created using different sensors and technologies to help navigate the blind. Electronic Travel AIDS (ETAs) assist in navigating a person by collecting information about the environment and relaying this information in a form that allows a blind or vision-impaired person to understand the nature of the environment. However, there is still a lack of devices to detect potholes and uneven pavements, which inhibits mobility after dark. This pilot study proposes a computer vision based pothole and uneven surface detection approach to assist blind people in meeting their mobility needs. The system includes projecting laser patterns, recording the patterns through a monocular video, analyzing the patterns to extract features and then providing path cues for the blind user. With over 90% accuracy in detecting potholes, the proposed system aims to assist blind people in real-time navigation.
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ItemNo Preview AvailableSecure multiple access for indoor optical wireless communications with time-slot coding and chaotic phase(OPTICAL SOC AMER, 2017-09-04)In this paper, we report a novel mechanism to simultaneously provide secure connections for multiple users in indoor optical wireless communication systems by employing the time-slot coding scheme together with chaotic phase sequence. The chaotic phase sequence is generated according to the logistic map and applied to each symbol to secure the transmission. Proof-of-concept experiments are carried out for multiple system capacities based on both 4-QAM and 16-QAM modulation formats, i.e. 1.25 Gb/s, 2 Gb/s and 2.5 Gb/s for 4-QAM, and 2.5 Gb/s, 3.33 Gb/s and 4 Gb/s for 16-QAM. Experimental results show that in all cases the added chaotic phase does not degrade the legitimate user's signal quality while the illegal user cannot detect the signal without the key.
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ItemAn Efficient Resource Allocation Mechanism for LTE-GEPON Converged Networks(SPRINGER, 2014-07)
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ItemNo Preview AvailableMobility-Aware Energy Optimization in Hosts Selection for Computation Offloading in Multi-Access Edge Computing(Institute of Electrical and Electronics Engineers (IEEE), 2020-07-15)Multi-access edge computing (MEC) has been proposed as an approach capable of addressing latency and bandwidth issues in application computation offloading to extend the capabilities beyond the computational and storage limitations of mobile devices. However, there is a critical challenge in MEC to maintain the service continuity between the offloaded user application that is running on the MEC host and the mobile device when a user is moving from radio node to radio node. Furthermore, energy consumption of application computation offloading is an important consideration for MEC service providers in terms of operational costs. Therefore, we formulate the MEC host selection and user application migration problem as a shortest path problem of network energy minimization. We simulate the problem in a hierarchical MEC network deployment environment. We also propose the metric, computational intensity (CI), that can be used by MEC service providers to address the MEC host selection problem. Our results show that with the increment of CI, the selection of MEC hosts tends to move toward level 3 (central deployment) due to energy efficiency and then return to the deployment at level 1 (radio node level) due to latency constraint of the user application. We show that with high accuracy in predicting the user mobility and the available resources in the MEC network, latency- and mobility-aware MEC host selection and user application migration can be pre-calculated to improve response time and energy efficiency.
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ItemEnabling Remote Human-to-Machine Applications With AI-Enhanced Servers Over Access Networks(Institute of Electrical and Electronics Engineers (IEEE), 2020)The recent research trends for achieving ultra-reliable and low-latency communication networks are largely driven by smart manufacturing and industrial Internet-of-Things applications. Such applications are being realized through Tactile Internet that allows users to control remote things and involve the bidirectional transmission of video, audio, and haptic data. However, the end-to-end propagation latency presents a stubborn bottleneck, which can be alleviated by using various artificial intelligence-based application layer and network layer prediction algorithms, e.g., forecasting and preempting haptic feedback transmission. In this paper, we study the experimental data on traffic characteristics of control signals and haptic feedback samples obtained through virtual reality-based human-to-machine teleoperation. Moreover, we propose the installation of edge-intelligence servers between master and slave devices to implement the preemption of haptic feedback from control signals. Harnessing virtual reality-based teleoperation experiments, we further propose a two-stage artificial intelligence-based module for forecasting haptic feedback samples. The first-stage unit is a supervised binary classifier that detects if haptic sample forecasting is necessary and the second-stage unit is a reinforcement learning unit that ensures haptic feedback samples are forecasted accurately when different types of material are present. Furthermore, by evaluating analytical expressions, we show the feasibility of deploying remote human-to-machine teleoperation over fiber backhaul by using our proposed artificial intelligence-based module, even under heavy traffic intensity.
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ItemGigabit/s Optical Wireless Access and Indoor Networks(OSA - Optical Society of America, 2020)Optical wireless networks are being explored as a wireless alternative for provision of multi gigabits/second wireless and this paper presents an overview of recent progress and outstanding challenges. and technologies.