Md. Tanvir Hossan

A Novel Indoor Mobile Localization System Based on Optical Camera Communication

Localizing smartphones in indoor environments offers excellent opportunities for e-commence. In this paper, we propose a localization technique for smartphones in indoor environments. This technique can calculate the coordinates of a smartphone using existing illumination infrastructure with light-emitting diodes (LEDs). The system can locate smartphones without further modification of the existing LED light infrastructure. Smartphones do not have fixed position and they may move frequently anywhere in an environment. Our algorithm uses multiple (i.e., more than two) LED lights simultaneously. The smartphone gets the LED-IDs from the LED lights that are within the field of view (FOV) of the smartphone’s camera. These LED-IDs contain the coordinate information (e.g., - and -coordinate) of the LED lights. Concurrently, the pixel area on the image sensor (IS) of projected image changes with the relative motion between the smartphone and each LED light which allows the algorithm to calculate the distance from the smartphone to that LED. At the end of this paper, we present simulated results for predicting the next possible location of the smartphone using Kalman filter to minimize the time delay for coordinate calculation. These simulated results demonstrate that the position resolution can be maintained within 10u2009cm.

A New Vehicle Localization Scheme Based on Combined Optical Camera Communication and Photogrammetry

The demand for autonomous vehicles is increasing gradually owing to their enormous potential benefits. However, several challenges, such as vehicle localization, are involved in the development of autonomous vehicles. A simple and secure algorithm for vehicle positioning is proposed herein without massively modifying the existing transportation infrastructure. For vehicle localization, vehicles on the road are classified into two categories: host vehicles (HVs) are the ones used to estimate other vehicles’ positions and forwarding vehicles (FVs) are the ones that move in front of the HVs. The FV transmits modulated data from the tail (or back) light, and the camera of the HV receives that signal using optical camera communication (OCC). In addition, the streetlight (SL) data are considered to ensure the position accuracy of the HV. Determining the HV position minimizes the relative position variation between the HV and FV. Using photogrammetry, the distance between FV or SL and the camera of the HV is calculated by measuring the occupied image area on the image sensor. Comparing the change in distance between HV and SLs with the change in distance between HV and FV, the positions of FVs are determined. The performance of the proposed technique is analyzed, and the results indicate a significant improvement in performance. The experimental distance measurement validated the feasibility of the proposed scheme.

Simplified photogrammetry using optical camera communication for indoor positioning

In this paper, we describe the positioning technique for camera based smartphone in an indoor environment. The camera of smartphone detects multiple light-emitting diode (LED) lights whose are located on the rooftop. LED light sends its coordinates (x, y) information to the camera whose are fixed and parallel to the world coordinate. We calculate the distance from each LED to the camera using photogrammetry. Later, a lighting server calculates the accurate position information and using extended Kalman filter algorithm it corrects position estimation error of the smartphone.

An Implementation Approach and Performance Analysis of Image Sensor Based Multilateral Indoor Localization and Navigation System

Optical camera communication (OCC) exhibits considerable importance nowadays in various indoor camera based services such as smart home and robot-based automation. An android smart phone camera that is mounted on a mobile robot (MR) offers a uniform communication distance when the camera remains at the same level that can reduce the communication error rate. Indoor mobile robot navigation (MRN) is considered to be a promising OCC application in which the white light emitting diodes (LEDs) and an MR camera are used as transmitters and receiver, respectively. Positioning is a key issue in MRN systems in terms of accuracy, data rate, and distance. We propose an indoor navigation and positioning combined algorithm and further evaluate its performance. An android application is developed to support data acquisition from multiple simultaneous transmitter links. Experimentally, we received data from four links which are required to ensure a higher positioning accuracy.

Adaptive spatial-temporal resolution optical vehicular communication system using image sensor

In this article, we introduce an image sensor–based optical vehicular communication system for performing vehicular condition resolution adaptively in the spatial domain and the temporal domain. To validate the proposed system, a dual camera–based approach is presented here, where a vision camera is used to detect multiple vehicles of interest (i.e. spatial condition), a communication link is set up, and then, a high-speed camera adapts its resolution to ensure fast processing and high-rate data communication (i.e. temporal condition). We suggest an adaptive algorithm that supports the detection of and communication multiple vehicles simultaneously in spatial-temporal condition. Moreover, we propose a combination of scale-invariant feature transform and iterative closest point for detection and classification of multiple vehicles. To prove the feasibility of our proposed scheme, we present simulation results.

Integrated RF/Optical Wireless Networks for Improving QoS in Indoor and Transportation Applications

Communications based solely on radio frequency (RF) networks cannot provide adequate quality of service for the rapidly growing demands of wireless connectivity. Since devices operating in the optical spectrum do not interfere with those using the RF spectrum, wireless networks based on the optical spectrum can be added to existing RF networks to fulfill this demand. Hence, optical wireless communication (OWC) technology can be an excellent complement to RF-based technology to provide improved service. Promising OWC systems include light fidelity (LiFi), visible light communication, optical camera communication (OCC), and free-space optical communication (FSOC). OWC and RF systems have differing limitations, and the integration of RF and optical wireless networks can overcome the limitations of both systems. This paper describes an LiFi/femtocell hybrid network system for indoor environments. Low signal-to-interference-plus-noise ratios and the shortage bandwidth problems of existing RF femtocell networks can be overcome with the proposed hybrid model. Moreover, we describe an integrated RF/optical wireless system that can be employed for users inside a vehicle, remote monitoring of ambulance patients, vehicle tracking, and vehicle-to-vehicle communications. We consider LiFi, OCC, and FSOC as the optical wireless technologies to be used for communication support in transportation, and assume macrocells, femtocells, and wireless fidelity to be the corresponding RF technologies. We describe handover management—including detailed call flow, interference management, link reliability improvement, and group handover provisioning—for integrated networks. Performance analyses demonstrate the significance of the proposed integrated RF/optical wireless systems.

Introduction of optical camera communication for Internet of vehicles (IoV)

In this paper, we have introduced optical camera communication (OCC) as a new technology for internet of vehicles (IoV). OCC has already been established in many areas which can also be used in vehicular communication. There have some researches in the field of OCC-based vehicular communication but these are not mature enough. Here, we have proposed a new system which will provide great advantages to the vehicular system. We proposed a combination of OCC and cloud-based communication for IoV which will ensure secure, stable, and system. We have also proposed an algorithm to provide cloud based IoV service.

Integration of photogrammetry and optical camera communication technologies for vehicle positioning

We propose an algorithm for vehicle positioning approach comparing the relative distance between street lights and forwarding vehicle. Rolling shutter CMOS (complementary metal-oxide-semiconductor) camera on the host vehicle detects the LED-ID (light-emitting diode-ID) from both the street LED lights and rear LED lights of the forwarding vehicles. The distance between vehicles can be measured by comparing the change of pixels on the image sensor of the camera. At the end of this paper, we provide simulation result to show the performance of our proposed scheme.