This document proposes a taxonomy for classifying different methods of ubiquitous positioning systems that can be used for location determination on mobile navigation systems. It identifies five key factors - scale, output, measurements, roles, and estimation method. For each factor, it outlines different options and provides examples from previous research. The taxonomy is intended to help researchers better understand the design options for ubiquitous positioning systems and to scope future research areas. It covers positioning methods based on radio frequency, vision, and GPS and categorizes them according to factors like the type of measurements used, system architecture, and algorithms for estimating location.
A Survey of Indoor Localization TechniquesIOSR Journals
This document provides a survey of indoor localization techniques. It begins by explaining that GPS cannot be used indoors due to lack of line of sight with satellites. It then classifies indoor localization techniques based on enabling technologies like radio frequency, ultrasound, wireless sensor networks, and smartphones. The document compares various techniques based on parameters like cost, accuracy, and provides a table comparing the results. It surveys localization techniques for applications like healthcare, asset tracking, and navigation indoors.
This document discusses location-based services (LBS) and evaluates different positioning techniques used in LBS. It begins by introducing common LBS applications and services. It then examines the components and architecture of LBS systems, including LBS middleware and location tracking. Privacy concerns with LBS are also addressed. The document evaluates and compares several positioning systems used in LBS, including satellite-based GPS, network-based methods like GSM, and indoor positioning techniques. It concludes by discussing limitations and opportunities for future work improving LBS positioning accuracy and privacy.
A genetic based indoor positioning algorithm using Wi-Fi received signal stre...IAESIJAI
The recent trend in location-based services has led to a proliferation of studies in indoor positioning technology. Wi-Fi received signal strength indicator (RSSI) Fingerprinting and pedestrian dead reckoning (PDR) are the two best representatives from both approaches. This research proposed a genetic algorithm to combine Wi-Fi Fingerprinting and PDR. By taking advantage of PDR and genetic algorithm, we only need to collect a limited number of points for the fingerprint dataset with known coordinates, then target trajectories' position can be estimated with high accuracy. Results from our experiments and simulations have shown that even in the scenario of noisy inertial measurement unit (IMU) sensors data, using RSSI measurements and the coordinate of 8 points, our proposed method was able to achieve 1.589 meters of average distance error which is 34.4 percent lower than the conventional Fingerprinting method.
The document proposes a framework that uses intelligent mobile devices to enable indoor wireless location tracking, navigation, and mobile augmented reality (AR). It discusses using mobile devices equipped with inertial measurement units (IMU) and multi-touch screens to provide user feedback to correct positioning errors. The framework also uses mobile AR through device cameras to help navigate users in complex 3D indoor environments and provide interactive location-based services. A prototype system was developed to demonstrate the feasibility of the proposed application framework.
A Survey of Privacy-Preserving Algorithms for Finding meeting point in Mobile...IJERA Editor
Location privacy in Location Based Services (LBS) is the capability to protect the connection between user’s identity, uncertainty sources, servers and database, thereby restraining an impending attacker from conveniently linking users of LBS to convinced locations. Smart Phones have become most important gadget for maintaining the daily activities, highly interconnected urban population is also increasingly dependent on these gadgets to regulate and schedule their daily lives. These applications often depend on current location of user or a class of user. Use of Smart Mapping technology is also increasing in large area; this system provides an easy attainable online platform that can be used for accessing many services. This survey paper projects the privacy-preserving algorithm to find the most favorable meeting location for a class of users. GSM calculates the location of all users.
Abstract: Wireless location finding is one of the key technologies for wireless sensor networks. GPS is the technology used but it can be used for the outdoor location. When we deal with the indoor locations GPS does not work. Indoor locations include buildings like supermarkets, big malls, parking, universities, and locations under the same roof. In these areas the accuracy of the GPS location is greatly reduced. Location showed on the map in not correct when the GPS is used under the indoor environments. But for the indoor localization it requires the higher accuracy sp GPS is not feasible for the current view. And also when the GPS is used in the mobile device it consumes a lot of the mobile battery to run the application which causes the drainage of the mobile battery within some hours. So to find out the accurate location for indoor environment we use the RSSI based trilateral localization algorithm. The algorithm has the low cost and the algorithm does not require any additional hardware support and moreover the algorithm is easy to understand. The algorithm consumes very less battery as compared to the battery consumption of the GPS. Because of these this algorithm has become the mainstream localization algorithm in the wireless sensor networks. With the development of the wireless sensor networks and the smart devices the WIFI access points are also increasing. The mobile smart devices detect three or more known WIFI hotspots positions. And using the values from the WIFI routers it calculates the current location of the mobile device. In this paper we have proposed a system so that we can find out the exact location of the mobile device under the indoor environment and can navigate to the destination using the navigation function and also can enable the low consumption of the smart mobile battery for the tracking purpose.
Goals:
1. Useful at the places where GPS cannot work
2. Reduces the battery consumption
3. Routers are used.
4. Provides the path as well as the information of the location as per the requirement of user.
WLAN BASED POSITIONING WITH A SINGLE ACCESS POINTijwmn
This document summarizes and compares different methods for WLAN-based positioning that can operate with a single access point (AP). It discusses the limitations of positioning with a single AP and classifies existing techniques into three categories: triangulation, triangulation and dead-reckoning fusion, and scene analysis and dead-reckoning fusion. It then compares techniques within each category based on criteria like positioning approach, additional sensor requirements, need for low-level information, sampling rate, user involvement, and site survey requirements. Specifically, it describes the Chronos positioning system which uses time-of-flight measurements between an AP and client to achieve decimeter-level accuracy with a single AP.
A one decade survey of autonomous mobile robot systems IJECEIAES
Recently, autonomous mobile robots have gained popularity in the modern world due to their relevance technology and application in real world situations. The global market for mobile robots will grow significantly over the next 20 years. Autonomous mobile robots are found in many fields including institutions, industry, business, hospitals, agriculture as well as private households for the purpose of improving day-to-day activities and services. The development of technology has increased in the requirements for mobile robots because of the services and tasks provided by them, like rescue and research operations, surveillance, carry heavy objects and so on. Researchers have conducted many works on the importance of robots, their uses, and problems. This article aims to analyze the control system of mobile robots and the way robots have the ability of moving in real-world to achieve their goals. It should be noted that there are several technological directions in a mobile robot industry. It must be observed and integrated so that the robot functions properly: Navigation systems, localization systems, detection systems (sensors) along with motion and kinematics and dynamics systems. All such systems should be united through a control unit; thus, the mission or work of mobile robots are conducted with reliability.
A Survey of Indoor Localization TechniquesIOSR Journals
This document provides a survey of indoor localization techniques. It begins by explaining that GPS cannot be used indoors due to lack of line of sight with satellites. It then classifies indoor localization techniques based on enabling technologies like radio frequency, ultrasound, wireless sensor networks, and smartphones. The document compares various techniques based on parameters like cost, accuracy, and provides a table comparing the results. It surveys localization techniques for applications like healthcare, asset tracking, and navigation indoors.
This document discusses location-based services (LBS) and evaluates different positioning techniques used in LBS. It begins by introducing common LBS applications and services. It then examines the components and architecture of LBS systems, including LBS middleware and location tracking. Privacy concerns with LBS are also addressed. The document evaluates and compares several positioning systems used in LBS, including satellite-based GPS, network-based methods like GSM, and indoor positioning techniques. It concludes by discussing limitations and opportunities for future work improving LBS positioning accuracy and privacy.
A genetic based indoor positioning algorithm using Wi-Fi received signal stre...IAESIJAI
The recent trend in location-based services has led to a proliferation of studies in indoor positioning technology. Wi-Fi received signal strength indicator (RSSI) Fingerprinting and pedestrian dead reckoning (PDR) are the two best representatives from both approaches. This research proposed a genetic algorithm to combine Wi-Fi Fingerprinting and PDR. By taking advantage of PDR and genetic algorithm, we only need to collect a limited number of points for the fingerprint dataset with known coordinates, then target trajectories' position can be estimated with high accuracy. Results from our experiments and simulations have shown that even in the scenario of noisy inertial measurement unit (IMU) sensors data, using RSSI measurements and the coordinate of 8 points, our proposed method was able to achieve 1.589 meters of average distance error which is 34.4 percent lower than the conventional Fingerprinting method.
The document proposes a framework that uses intelligent mobile devices to enable indoor wireless location tracking, navigation, and mobile augmented reality (AR). It discusses using mobile devices equipped with inertial measurement units (IMU) and multi-touch screens to provide user feedback to correct positioning errors. The framework also uses mobile AR through device cameras to help navigate users in complex 3D indoor environments and provide interactive location-based services. A prototype system was developed to demonstrate the feasibility of the proposed application framework.
A Survey of Privacy-Preserving Algorithms for Finding meeting point in Mobile...IJERA Editor
Location privacy in Location Based Services (LBS) is the capability to protect the connection between user’s identity, uncertainty sources, servers and database, thereby restraining an impending attacker from conveniently linking users of LBS to convinced locations. Smart Phones have become most important gadget for maintaining the daily activities, highly interconnected urban population is also increasingly dependent on these gadgets to regulate and schedule their daily lives. These applications often depend on current location of user or a class of user. Use of Smart Mapping technology is also increasing in large area; this system provides an easy attainable online platform that can be used for accessing many services. This survey paper projects the privacy-preserving algorithm to find the most favorable meeting location for a class of users. GSM calculates the location of all users.
Abstract: Wireless location finding is one of the key technologies for wireless sensor networks. GPS is the technology used but it can be used for the outdoor location. When we deal with the indoor locations GPS does not work. Indoor locations include buildings like supermarkets, big malls, parking, universities, and locations under the same roof. In these areas the accuracy of the GPS location is greatly reduced. Location showed on the map in not correct when the GPS is used under the indoor environments. But for the indoor localization it requires the higher accuracy sp GPS is not feasible for the current view. And also when the GPS is used in the mobile device it consumes a lot of the mobile battery to run the application which causes the drainage of the mobile battery within some hours. So to find out the accurate location for indoor environment we use the RSSI based trilateral localization algorithm. The algorithm has the low cost and the algorithm does not require any additional hardware support and moreover the algorithm is easy to understand. The algorithm consumes very less battery as compared to the battery consumption of the GPS. Because of these this algorithm has become the mainstream localization algorithm in the wireless sensor networks. With the development of the wireless sensor networks and the smart devices the WIFI access points are also increasing. The mobile smart devices detect three or more known WIFI hotspots positions. And using the values from the WIFI routers it calculates the current location of the mobile device. In this paper we have proposed a system so that we can find out the exact location of the mobile device under the indoor environment and can navigate to the destination using the navigation function and also can enable the low consumption of the smart mobile battery for the tracking purpose.
Goals:
1. Useful at the places where GPS cannot work
2. Reduces the battery consumption
3. Routers are used.
4. Provides the path as well as the information of the location as per the requirement of user.
WLAN BASED POSITIONING WITH A SINGLE ACCESS POINTijwmn
This document summarizes and compares different methods for WLAN-based positioning that can operate with a single access point (AP). It discusses the limitations of positioning with a single AP and classifies existing techniques into three categories: triangulation, triangulation and dead-reckoning fusion, and scene analysis and dead-reckoning fusion. It then compares techniques within each category based on criteria like positioning approach, additional sensor requirements, need for low-level information, sampling rate, user involvement, and site survey requirements. Specifically, it describes the Chronos positioning system which uses time-of-flight measurements between an AP and client to achieve decimeter-level accuracy with a single AP.
A one decade survey of autonomous mobile robot systems IJECEIAES
Recently, autonomous mobile robots have gained popularity in the modern world due to their relevance technology and application in real world situations. The global market for mobile robots will grow significantly over the next 20 years. Autonomous mobile robots are found in many fields including institutions, industry, business, hospitals, agriculture as well as private households for the purpose of improving day-to-day activities and services. The development of technology has increased in the requirements for mobile robots because of the services and tasks provided by them, like rescue and research operations, surveillance, carry heavy objects and so on. Researchers have conducted many works on the importance of robots, their uses, and problems. This article aims to analyze the control system of mobile robots and the way robots have the ability of moving in real-world to achieve their goals. It should be noted that there are several technological directions in a mobile robot industry. It must be observed and integrated so that the robot functions properly: Navigation systems, localization systems, detection systems (sensors) along with motion and kinematics and dynamics systems. All such systems should be united through a control unit; thus, the mission or work of mobile robots are conducted with reliability.
This document proposes a user-centric approach called MobiCrowd to improve location privacy in location-based services. MobiCrowd allows mobile users to collaborate by storing each other's location information and responding to queries, hiding users from the location server unless no collaborative peers have the requested information. An epidemic model is developed to analyze how parameters like query rates and data lifetime affect privacy. Results show MobiCrowd hides a high fraction of queries, significantly enhancing privacy, and implementation shows it is lightweight with negligible collaboration costs.
The proposed System for Indoor Location TrackingEditor IJCATR
Indoor location tracking systems are used to locate people or certain objects in buildings and in closed areas. For example,
finding co-workers in a large office building, locating customers within a shopping mall and locating patients in the hospital are a few
applications of indoor location tracking systems. Indoor tracking capability opens up multiple possibilities. To address this need, this
paper describes the implementation of a Bluetooth-based indoor location tracking system that utilizes the integrated Bluetooth modules
in any today's mobile phones to specify and display the location of the individuals in a certain building. The proposed system aims for
location tracking/monitoring and marketing applications for whom want to locate individuals carrying mobile phones and advertise
products and services.
Indoor localization Leveraging Human Perception of Textual SignsShekhar Vimalendu
The document describes an offline indoor localization system that uses human perception of textual signs. It leverages the large number of textual signs inside buildings to guide visitors. The system stores signs and their corresponding coordinates in a database. When a user identifies the nearest sign, the sign is queried in the database to determine the user's location. The system was implemented as an Android application that allows users to select signs from a list, without requiring any infrastructure support. It was tested inside a university building and correctly identified locations near signs with 100% accuracy. The system provides an alternative for indoor localization without needing dedicated hardware.
This document summarizes an object tracking system that uses RF transmitters attached to objects, receivers to detect the transmitted signals, and a mobile phone interface. Objects are tagged with unique IDs. When an object enters a receiver's range, its ID and location are stored in a database. Users can query an object's location by sending an SMS message via a GSM modem connected to the database. The modem retrieves the object's location and description from the database and sends it back in a return SMS. The system allows users to track objects entering or leaving receiver ranges and locate objects on demand. It provides a low-cost infrastructure for wide-area object tracking using existing cellular networks.
A survey on hiding user privacy in location based services through clusteringeSAT Journals
Abstract Smartphone’s are being more and more popular as the technology being evolve. The Smartphone’s are capable of providing the location aware services like GPS. They share all the location information with the central location server. When user submit any query then these query also carries some personal information of the user. This query and information is then submitted to the LGS server. At the LBS server this information is not much confidential. Someone can use this information to make user panic. To overcome this we are proposing the new collaborative approach to hide user’s personal data from the LBS server. Our approach does not lead to make changes in the architecture of the LBS server. And we are also not going to use the third party server. Here we are going to use the other user’s device to search other users query so that other user can be get hide from the LBS server. Keywords: Mobile networks, location-based services, location privacy, Bayesian inference attacks, epidemic models
The document summarizes a study on using Wi-Fi signals for indoor location fingerprinting. It discusses how fingerprinting involves two phases: a calibration phase where signal strength is recorded at calibration points, and a location estimation phase where current signal strength is compared to the fingerprint map. It evaluates the k-nearest neighbor algorithm using Euclidean, Manhattan, and Chebychev distances to estimate location. Tests of this approach involved collecting Wi-Fi signal data at calibration points in four rooms and a hall to generate a fingerprint map for location estimation. The accuracy of Euclidean and Manhattan distances was found to be better than Chebychev distance for this location fingerprinting method.
The document summarizes a study on using Wi-Fi signals for indoor location fingerprinting. It discusses how fingerprinting involves two phases: a calibration phase where signal strength is recorded at calibration points, and a location estimation phase where current signal strength is compared to the fingerprint map. It evaluates the k-nearest neighbor algorithm using Euclidean, Manhattan, and Chebychev distances to estimate location. Tests of this approach involved collecting Wi-Fi signal data at calibration points in four rooms and a hall to generate a fingerprint map for location estimation. The accuracy of Euclidean and Manhattan distances was found to be better than Chebychev distance for this location fingerprinting method.
Smartphone indoor positioning based on enhanced BLE beacon multi-laterationTELKOMNIKA JOURNAL
In this paper, we introduce a smartphone indoor positioning method using bluetooth low energy (BLE) beacon multilateration. At first, based on signal strength analysis, we construct a distance calculation model for BLE beacons. Then, with the aims to improve positioning accuracy, we propose an improved lateral method (range-based method) which is applied for 4 nearby beacons. The method is intended to design a real-time system for some services such as emergency assistance, personal localization and tracking, location-based advertising and marketing, etc. Experimental results show that the proposed method achieves high accuracy when compared with the state of the art lateral methods such as geometry-based (conventional trilateration), least square estimation-based (LSE-based) and weighted LSE-based.
5G VS WI-FI INDOOR POSITIONING: A COMPARATIVE STUDYIJCSES Journal
Sensing location information in indoor scenes requires a high accuracy and is a challenging task, mainly
because of multipath and NLoS (non-line-of-sight) propagation. GNSS signals cannot penetrate well in
indoor environment. Satellite-based navigation and positioning systems cannot therefore be used for indoor
positioning.. Other technologies have been suggested for indoor usage, among them, Wi-Fi (802.11) and
5G NR (New Radio). The primary aim of this study is to discuss the advantages and drawbacks of 5G and
Wi-Fi positioning techniques for indoor localization
5G Vs Wi-Fi Indoor Positioning: A Comparative StudyIJCSES Journal
Sensing location information in indoor scenes requires a high accuracy and is a challenging task, mainly because of multipath and NLoS (non-line-of-sight) propagation. GNSS signals cannot penetrate well in indoor environment. Satellite-based navigation and positioning systems cannot therefore be used for indoor positioning. Other technologies have been suggested for indoor usage, among them, Wi-Fi (802.11) and 5G NR (New Radio). The primary aim of this study is to discuss the advantages and drawbacks of 5G and Wi-Fi positioning techniques for indoor localization.
Nuzzer algorithm based Human Tracking and Security System for Device-Free Pas...Eswar Publications
In recent years, majority of researches are focused on localization system for wireless environment. These researches rely on localization using devices to track the entities. In this paper, we use, a recently proposed Device-free Passive (DfP) that uses Probabilistic techniques to track locations in large-scale real environment without the need of carrying devices. The proposed system uses the Access Points (APs) and Monitoring Point (MPs) that works by monitoring and processing the changes in the received physical signals at one or more monitoring points to detect changes in the environment. The system uses continuous space estimator to return multiple location while the mortal is in motion. Our results show that the system can achieve very high probability of detection and tracking with very few false positives.
Intelligent GIS-Based Road Accident Analysis and Real-Time Monitoring Automat...CSCJournals
This document summarizes an intelligent road accident analysis and monitoring system that uses GIS, WiMAX/GPRS, and location-based services. The system aims to help reduce road accidents by allowing real-time accident reporting and response. It collects accident data using mobile devices and transfers it to a database via wireless networks. The data is then analyzed using statistical reports, decision making tools, and smart diagnosis to identify accident patterns and recommend safety solutions. The system is intended to help police respond faster to accidents and notify other emergency services.
Survey of indoor tracking systems using augmented realityIAESIJAI
Augmented reality overlays virtual content on the physical world, displaying location-based information more efficiently. Tracking is a trace detail of the location recorded, either by taking a reading based on a set time interval, set distance, and change in direction by more than a certain angle, or a combination of these. Tracking is divided into two types, outdoor tracking, and indoor tracking. Augmented reality added value and information to tracking applications, whether indoor or outdoor. Recently, outdoor tracking by the global positioning system (GPS) became an essential component in navigation applications. However, indoor tracking is still challenging in the augmented reality field. Most augmented reality indoor tracking use optical and sensor-based tracking, such as markers, beacons, Raspberry Pi, and
route planner modules for the building. With the technology enhancement, indoor tracking started to rely on Wi-Fi, Bluetooth, geographic information system, radiofrequency identification, and sensor chip technologies. Our paper describes the recent augmented reality tracking techniques from 2011 to 2021. The paper compares image detection algorithms with various communication technologies, disscusing the advantages and the limitations of each technology.
a data mining approach for location production in mobile environments marwaeng
The document proposes a three-phase algorithm for predicting the next location of mobile users. In the first phase, mobility patterns are mined from historical user trajectory data. In the second phase, mobility rules are extracted from these patterns. In the third phase, predictions are made by matching mobility rules to a user's current trajectory. The algorithm aims to overcome limitations of prior work by discovering regular patterns in user movements and distinguishing between random and regular movements. A simulation evaluation found the proposed method achieved more accurate predictions than other methods.
The document discusses implementing geo-messaging on Android using Google Cloud Messaging (GCM) and Location Based Services APIs. It proposes an application that sends messages to users when they are near a specified location using geo-fencing. The application uses GCM to push messages from a server to devices and Location Services to detect when devices enter or exit geo-fenced areas to trigger message delivery. The document outlines the system architecture, registration process, geo-fencing implementation, and concludes discussing potential future applications of location-based services.
The document discusses enhancing indoor localization using IoT techniques. It proposes a framework that uses a quaternion-based extended Kalman filter for heading estimation in pedestrian dead reckoning (PDR), along with low pass filtering and adaptive step length methodology. This approach achieved an average error of 0.16 meters, representing 0.07% of the total 210 meters traveled in experiments. The document also discusses using IoT devices to further improve indoor localization accuracy.
An Enhanced Predictive Proportion using TMP Algorithm in WSN NavigationIJCERT
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ASSESSMENT OF ALTERNATIVE PRECISION POSITIONING SYSTEMSijitcs
The continuous evolution of technology, electronics, and software along with the dramatic decrease in the
cost of electronic devices has led to the spread of sensing, surveillance, and control devices. The Internetof-Things
(IoT) benefits from the spread of devices (things) by processing device feeds using Machine-toMachine
(M2M) technologies. At the heart of the M2M technologies lies the ability of devices (things) to identify their own location on the globe or relative to known landmark. Since location awareness is fundamental to processing sensing and control feeds, it has attracted researchers to identify ways to
identify and improve location accuracy. The article looks at Global Positioning Systems (GPS) along with the enhancements and amendments that apply to satellite based solutions. The article also looks at medium to short-range wireless solutions such as cellular, Wi-Fi, Dedicated Short-Range Communications (5.9 GHz DSRC) and similar solutions.
In this project, we describe a unique architecture for indoor navigation that integrates behavior recognition, multisensory indoor localization, and path-planning in order to pro-actively provide directions without direct input from users. To our knowledge, this is the first architecture that attempts to integrate the core navigation components of path planning and localization with intent prediction towards a more refined navigation solution. The system comprises of three core components: augmented reality, map representation and route planning, and plan recognition.
To achieve effective localization, we provide pre-built maps using QR code scanning distributed at various places of the indoor location. We are using Augmented Reality to make an intuitive and user friendly interface which uses QR codes for identification of various maps that are pre uploaded in the QR codes for the ease of users.
LOCALIZATION ALGORITHM USING VARYING SPEED MOBILE SINK FOR WIRELESS SENSOR NE...ijasuc
Localization of sensor nodes is important in many aspects in wireless sensor networks. The known
location of sensor node helps in determining the event of interest. A mobile sink is introduced to track the
event driven sensor nodes in the path of the event, thus conserving energy and time. We present a novel
range based localization algorithm which helps the mobile sink to compute the location of the sensor
nodes efficiently. The data transfer from the mobile sink and the sensor nodes is used to estimate the
sensor location. The sensor nodes do not need to spend energy on neighbouring interaction for
localization. The localization mechanism has been implemented in TOSSIM. The simulation results show
that our scheme performed better than other range-based schemes.
This document proposes a user-centric approach called MobiCrowd to improve location privacy in location-based services. MobiCrowd allows mobile users to collaborate by storing each other's location information and responding to queries, hiding users from the location server unless no collaborative peers have the requested information. An epidemic model is developed to analyze how parameters like query rates and data lifetime affect privacy. Results show MobiCrowd hides a high fraction of queries, significantly enhancing privacy, and implementation shows it is lightweight with negligible collaboration costs.
The proposed System for Indoor Location TrackingEditor IJCATR
Indoor location tracking systems are used to locate people or certain objects in buildings and in closed areas. For example,
finding co-workers in a large office building, locating customers within a shopping mall and locating patients in the hospital are a few
applications of indoor location tracking systems. Indoor tracking capability opens up multiple possibilities. To address this need, this
paper describes the implementation of a Bluetooth-based indoor location tracking system that utilizes the integrated Bluetooth modules
in any today's mobile phones to specify and display the location of the individuals in a certain building. The proposed system aims for
location tracking/monitoring and marketing applications for whom want to locate individuals carrying mobile phones and advertise
products and services.
Indoor localization Leveraging Human Perception of Textual SignsShekhar Vimalendu
The document describes an offline indoor localization system that uses human perception of textual signs. It leverages the large number of textual signs inside buildings to guide visitors. The system stores signs and their corresponding coordinates in a database. When a user identifies the nearest sign, the sign is queried in the database to determine the user's location. The system was implemented as an Android application that allows users to select signs from a list, without requiring any infrastructure support. It was tested inside a university building and correctly identified locations near signs with 100% accuracy. The system provides an alternative for indoor localization without needing dedicated hardware.
This document summarizes an object tracking system that uses RF transmitters attached to objects, receivers to detect the transmitted signals, and a mobile phone interface. Objects are tagged with unique IDs. When an object enters a receiver's range, its ID and location are stored in a database. Users can query an object's location by sending an SMS message via a GSM modem connected to the database. The modem retrieves the object's location and description from the database and sends it back in a return SMS. The system allows users to track objects entering or leaving receiver ranges and locate objects on demand. It provides a low-cost infrastructure for wide-area object tracking using existing cellular networks.
A survey on hiding user privacy in location based services through clusteringeSAT Journals
Abstract Smartphone’s are being more and more popular as the technology being evolve. The Smartphone’s are capable of providing the location aware services like GPS. They share all the location information with the central location server. When user submit any query then these query also carries some personal information of the user. This query and information is then submitted to the LGS server. At the LBS server this information is not much confidential. Someone can use this information to make user panic. To overcome this we are proposing the new collaborative approach to hide user’s personal data from the LBS server. Our approach does not lead to make changes in the architecture of the LBS server. And we are also not going to use the third party server. Here we are going to use the other user’s device to search other users query so that other user can be get hide from the LBS server. Keywords: Mobile networks, location-based services, location privacy, Bayesian inference attacks, epidemic models
The document summarizes a study on using Wi-Fi signals for indoor location fingerprinting. It discusses how fingerprinting involves two phases: a calibration phase where signal strength is recorded at calibration points, and a location estimation phase where current signal strength is compared to the fingerprint map. It evaluates the k-nearest neighbor algorithm using Euclidean, Manhattan, and Chebychev distances to estimate location. Tests of this approach involved collecting Wi-Fi signal data at calibration points in four rooms and a hall to generate a fingerprint map for location estimation. The accuracy of Euclidean and Manhattan distances was found to be better than Chebychev distance for this location fingerprinting method.
The document summarizes a study on using Wi-Fi signals for indoor location fingerprinting. It discusses how fingerprinting involves two phases: a calibration phase where signal strength is recorded at calibration points, and a location estimation phase where current signal strength is compared to the fingerprint map. It evaluates the k-nearest neighbor algorithm using Euclidean, Manhattan, and Chebychev distances to estimate location. Tests of this approach involved collecting Wi-Fi signal data at calibration points in four rooms and a hall to generate a fingerprint map for location estimation. The accuracy of Euclidean and Manhattan distances was found to be better than Chebychev distance for this location fingerprinting method.
Smartphone indoor positioning based on enhanced BLE beacon multi-laterationTELKOMNIKA JOURNAL
In this paper, we introduce a smartphone indoor positioning method using bluetooth low energy (BLE) beacon multilateration. At first, based on signal strength analysis, we construct a distance calculation model for BLE beacons. Then, with the aims to improve positioning accuracy, we propose an improved lateral method (range-based method) which is applied for 4 nearby beacons. The method is intended to design a real-time system for some services such as emergency assistance, personal localization and tracking, location-based advertising and marketing, etc. Experimental results show that the proposed method achieves high accuracy when compared with the state of the art lateral methods such as geometry-based (conventional trilateration), least square estimation-based (LSE-based) and weighted LSE-based.
5G VS WI-FI INDOOR POSITIONING: A COMPARATIVE STUDYIJCSES Journal
Sensing location information in indoor scenes requires a high accuracy and is a challenging task, mainly
because of multipath and NLoS (non-line-of-sight) propagation. GNSS signals cannot penetrate well in
indoor environment. Satellite-based navigation and positioning systems cannot therefore be used for indoor
positioning.. Other technologies have been suggested for indoor usage, among them, Wi-Fi (802.11) and
5G NR (New Radio). The primary aim of this study is to discuss the advantages and drawbacks of 5G and
Wi-Fi positioning techniques for indoor localization
5G Vs Wi-Fi Indoor Positioning: A Comparative StudyIJCSES Journal
Sensing location information in indoor scenes requires a high accuracy and is a challenging task, mainly because of multipath and NLoS (non-line-of-sight) propagation. GNSS signals cannot penetrate well in indoor environment. Satellite-based navigation and positioning systems cannot therefore be used for indoor positioning. Other technologies have been suggested for indoor usage, among them, Wi-Fi (802.11) and 5G NR (New Radio). The primary aim of this study is to discuss the advantages and drawbacks of 5G and Wi-Fi positioning techniques for indoor localization.
Nuzzer algorithm based Human Tracking and Security System for Device-Free Pas...Eswar Publications
In recent years, majority of researches are focused on localization system for wireless environment. These researches rely on localization using devices to track the entities. In this paper, we use, a recently proposed Device-free Passive (DfP) that uses Probabilistic techniques to track locations in large-scale real environment without the need of carrying devices. The proposed system uses the Access Points (APs) and Monitoring Point (MPs) that works by monitoring and processing the changes in the received physical signals at one or more monitoring points to detect changes in the environment. The system uses continuous space estimator to return multiple location while the mortal is in motion. Our results show that the system can achieve very high probability of detection and tracking with very few false positives.
Intelligent GIS-Based Road Accident Analysis and Real-Time Monitoring Automat...CSCJournals
This document summarizes an intelligent road accident analysis and monitoring system that uses GIS, WiMAX/GPRS, and location-based services. The system aims to help reduce road accidents by allowing real-time accident reporting and response. It collects accident data using mobile devices and transfers it to a database via wireless networks. The data is then analyzed using statistical reports, decision making tools, and smart diagnosis to identify accident patterns and recommend safety solutions. The system is intended to help police respond faster to accidents and notify other emergency services.
Survey of indoor tracking systems using augmented realityIAESIJAI
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An Enhanced Predictive Proportion using TMP Algorithm in WSN NavigationIJCERT
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Ubiquitous Positioning: A Taxonomy for Location Determination on Mobile Navigation System
1. Signal & Image Processing : An International Journal(SIPIJ) Vol.2, No.1, March 2011
DOI : 10.5121/sipij.2011.2103 24
Ubiquitous Positioning: A Taxonomy for
Location Determination on Mobile Navigation
System
Wan Bejuri, Wan Mohd. Yaakob1
, Mohamad, Mohd. Murtadha1
and Sapri,
Maimunah2
1
Faculty of Computer Science & Information Systems,
Universiti Teknologi Malaysia, Johor, Malaysia
wanmohdyaakob@gmail.com, murtadha@utm.my
2
Faculty of Geoinformation & Real Estate,
Universiti Teknologi Malaysia, Johor, Malaysia
maimunahsapri@utm.my
ABSTRACT
The location determination in obstructed area can be very challenging especially if Global Positioning
System are blocked. Users will find it difficult to navigate directly on-site in such condition, especially
indoor car park lot or obstructed environment. Sometimes, it needs to combine with other sensors and
positioning methods in order to determine the location with more intelligent, reliable and ubiquity. By
using ubiquitous positioning in mobile navigation system, it is a promising ubiquitous location technique
in a mobile phone since as it is a familiar personal electronic device for many people. However, there is
an increasing need for better development of proposed ubiquitous positioning systems. System developers
are also lacking of good frameworks for understanding different options during building ubiquitous
positioning systems. This paper proposes taxonomy to address both of these problems. The proposed
taxonomy has been constructed from a literature study of papers and articles on positioning estimation
that can be used to determine location everywhere on mobile navigation system. For researchers the
taxonomy can also be used as an aid for scoping out future research in the area of ubiquitous positioning.
KEYWORDS
Ubiquitous Positioning, Mobile Navigation System, Location Determination
1. INTRODUCTION
Nowadays, the usage of GPS smart phone is increasingly widespread. It is because the
capability of the smart phone can be used as personal navigator and communicator device.
There are so many mobile navigation techniques which can be utilized to determine location
which one of them is by using GPS which is already embedded in current GPS mobile phone.
By using standalone GPS (ex: GPS smart phone), it is impossible to get better accuracy or
signal especially in the particular obstructed environment (for ex: indoor car park, office,
building, school and etc.). In addition, the object such as tree, high building, high wall and also
people walking might be the contributors of the obstruction. These obstructions sometimes
moved to another location which usually happened in indoor environment and finally make it
difficult to estimate user’s position. Moreover, the usage of other sensor on mobile phone such
as WLAN, Bluetooth, GSM, and camera can be exploited to be alternative positioning sensor in
order to determine user positioning in case if the GPS failed. Previous studies on mobile
navigation system are focusing more on single sensor positioning and integration with external
sensor. The integration with external sensor mostly is quite successful on positioning accuracy,
2. Signal & Image Processing : An International Journal(SIPIJ) Vol.2, No.1, March 2011
25
but it is not really successful in terms of mobility. Moreover, the use of single positioning is also
seems successful in mobility but however failed in ubiquity. The system’s lacking of ubiquity is
actually due to the lack of sensor integration within mobile phone. Thus, mobile positioning
technologies need to be taxon or categorized together before the development of a reliable
mobile navigation system.
The structure of the paper is as follows. Section 2 will present the reviews related work to
taxonomy of location determination. Section 3 will present an overview of the proposed
taxonomy. The detail of the proposed taxonomy will be covered in section 3.2. This will be
followed by an exploratory of location determination taxon on radio frequency based, vision
based and GPS based that are discussed in section 3.2, 3.2.1, 3.2.2, and 3.2.3. Finally,
conclusions are given in section 4.
2. RELATED WORK
Most previous works focused on constructing taxonomies of location determination techniques
by using specific type of positioning sensor. In an article describing the location systems for
ubiquitous computing, Hightower et al., (2001) [1] have developed a taxonomy for mobile
computing devices in order to identify opportunities for new location-sensing techniques.
Several evaluation properties have been listed: precision, accuracy, scale, cost, and limitations.
However, taxonomy that was proposed by Hightower et al., (2001) [1] has been
criticised by Kjaergaard (2007) [2]. Kjaergaard (2007) [2] stated that it was not much help in
specific question to radio location fingerprinting by proposing specific taxonomy for general
properties of location fingerprinting systems which are: scale, output, measurements, and
roles. Moreover, in an article describing the survey of wireless indoor positioning, Liu et al.,
(2007) [3] have developed a taxonomy for performance of wireless indoor positioning based on
[4] by listing: accuracy, precision, complexity, robustness, scalability and cost. Furthermore, the
list was improvised by Gu et al. (2009) [5] in her article by introducing several evaluation
criteria for assessing indoor positioning systems, namely security and privacy, cost,
performance, robustness, complexity, user preferences, commercial availability, and limitations.
3. TAXONOMY
The proposed taxonomy is built around five (5) taxons listed each with definition in Table 1.
This taxonomy is originated from Kjærgaard [2] that introduce taxonomy for radio location
fingerprinting, but we enhance it by scoping for mobile positioning technologies (such as: GPS,
Vision, WiFi, Bluetooth, and GSM). These were partly inspired by earlier work on taxonomies
for location systems in general and from our literature study. The four taxons: scale, output,
measurements, and roles describe general properties of mobile navigation systems.
Figure 1. Taxon Definition
Taxon Definition
Scale Size of deployment area.
Output Type of provided location information.
Measurements Types of measured input signal from positioning sensor.
Roles Division of positioning system architecture
Estimation Method Algorithm that is used to estimate positioning information
from measured input signal.
3. Signal & Image Processing : An International Journal(SIPIJ) Vol.2, No.1, March 2011
26
The focus of the proposed taxonomy is on methods for location determination in mobile
positioning technology that can be used on mobile navigation system. The evaluation properties
such as in article Hightower [1] and Lie et al, [3] will be not covered in this paper.
3.1. General Taxon
The general taxons that proposed in Kjærgaard [2] are improved based on our scope. These
taxons are shown in Figure 2 including subtaxons. In this following sections, taxons are
presented up to four (4) references are given to papers or articles that propose systems that are
grouped below the particular taxon.
Figure 2. Scale, Output, Measurements and Roles (Kjærgaard [2], Sun et al, [6], Raviv et al, [7],
Savarese et al, [8], Gavrila et al, [9], Rohrmus [10], Liapis et al, [11], Post et al, [12], Blake et al,
[13], Aponte et al, [14], Neri et al, [15], Manodham et al, [16], Norouzi et al, [17], Aktas et al, [18])
Scale
Building
City
Campus
Output
Descriptive
Spatial
Radio Frequency (WLAN,
Bluetooth & GSM)
Base Station Identifier (BSI)
Signal-to-Noise Ratio (SNR)
Received Signal Strength (RSS)
Link Quality Indication (LQI)
Power Level
Response Rate (RR)
L1 signal
Measurements
Direct Flow (ex: Colour)
Geometric flow (ex: Corner, Vertical Edge)
Texture-based Flow
Feature-based flow
Visualization (Camera)
GPS
Terminal-based
Infrastructure-
based
Terminal-assisted
Network-based
Infrastructure-
less
Terminal-based
Collaborative
Radio Frequency (WLAN,
Bluetooth & GSM)
Roles GPS
Standalone
Network-based
Standalone
Visualization (Camera)
Collaborative
4. Signal & Image Processing : An International Journal(SIPIJ) Vol.2, No.1, March 2011
27
Figure 2 displays the four (4) factors necessitating identification, which are scale, measurement,
output and roles. Scale refers to the size of a system’s deployment, which is essential as it
affects data collection and the scale constraints of certain systems due to particular assumptions.
Output refers to the categories of location information, of which there are two. The first is
descriptive locations, which are expressed in the form of object-allocated variables or
identifiers; the second is spatial locations, which are expressed as a set of coordinates that
correspond with a spatial reference system.
Measurements refer to the type of measured input signal from positioning sensor. For radio
frequency positioning (WLAN, Bluetooth and GSM), the measurement technique can be used
such as: Base Station Identifiers (BSI), Received Signal Strength (RSS), Signal-to-Noise Ratio
(SNR), Link Quality Indicator (LQI), Power Level (PL), and Response Rate (RR). BSI is a
name distinctively allotted for a base station, while RSS, SNR, and LQI are radio-obtained
signal propagation metrics utilized to manage and optimize communication. PL signifies the
information regarding the present sending power that is sent by the signal sender, and RR refers
to the frequency of obtained measurements sent by a particular base station throughout a certain
temporal period. For GPS, L1 is needed in order to obtain input signal measurement. For vision
technology, direct flow, texture-based flow, geometric flow, and feature-based flow can be
utilized. This vision measurement is a low level image detection technique.
Roles explain the allocation about division of positioning system architecture. As for radio
frequency positioning such as WLAN, Bluetooth and GSM, it is presented in two (2) types; the
first is infrastructure-based systems, which rely on a pre-installed powered infrastructure of base
stations. The second is known as infrastructure-less system that encompass of ad-hoc-installed
battery-powered wireless clients, with some undertake the function of base stations. For GPS, it
is presented in two (2) types which are standalone and network-based. Standalone is a system
architecture which involves single GPS observation, while network-based involves more than
one (1) GPS observation. For vision technology, it is presented in two (2) types which are
standalone and collaborative. Standalone is a system architecture which involves single camera
observation, while collaborative involves more than one (1) camera observation. Usually
collaborative technique used involves three (3) dimension measurement or for reducing error.
3.2. Location Estimation Taxon
Figure 2.3 depicts the location estimation method used for predicting locations. However, it is
very challenging to taxonomize all possible methods because nearly all methods developed for
machine learning (Sun et al, [6]) (see Witten et al, [19] for a list of methods) or in the field of
estimation (see Crassidis et al, [20] for a list of methods) are applicable to the problem of
location estimation. On another note, numerous researches have also been carried out regarding
location estimation previously. In this paper, we follow Liu et al, [21] for radio frequency
positioning, Bonin-Font et al, [22] for camera navigation and Quddus et al, [23] for GPS.
5. Signal & Image Processing : An International Journal(SIPIJ) Vol.2, No.1, March 2011
28
Figure 3. Location Estimation Method (Kjærgaard [2], Liu et al, [21], Bonin-Font et al, [22], Quddus et
al, [23])
Camera based
Map-based
Map-building-
Mapless
Scene Analysis
Offline Mode
Online Mode
Probabilistic
Method
kNN
Neural Network
SVM
SMP
Empirical
Deterministi
Outlier
Direct
Interpolation
Aggregation
Probabilistic
Interpolation
Aggregation
Model-
Parameters
Estimated
A Priori
Propagation
Direct Path
Ray
Representati
Deterministic
Probabilistic
Radio Frequency based
Triangulation
Lateration Technique
TOA
TDOA
RSS
RTOF
Received Single
Phase
Angulation
Technique
AOA
GPS
Geometric Map
Topological Map
Probabilistic Map
Advanced Map Matching
6. Signal & Image Processing : An International Journal(SIPIJ) Vol.2, No.1, March 2011
29
3.2.1. Radio Frequency Based
Radio frequency positioning estimation technique is split into the two (2) categories of scence
analysis and triangulation. Scene analysis refers to the type of algorithms that first collect
features (fingerprints) of a scene and then estimate the location of an object by matching online
measurements with the closest a priori location fingerprints. There are two phases for location
fingerprinting: offline stage and online stage (or run-time stage). A site survey is performed in
an environment during the offline stage. The location coordinates/labels and respective signal
strengths from nearby base stations/measuring units are collected (see algorithm example in
figure 3). During the online stage, a location positioning technique uses the currently observed
signal strengths and previously collected information to figure out an estimated location (see
algorithm example in figure 3). Triangulation uses the geometric properties of triangles to
estimate the target location. It has two derivations: lateration and angulation. Lateration
estimates the position of an object by measuring its distances from multiple reference points
(see example algorithm). So, it is also called range measurement techniques. Angulation locates
an object by computing angles relative to multiple reference points (see example algorithm at
Van Veen et al, [24], Stoica et al, [25], Ottersten et al, [26]).
3.2.2 Camera Navigation Based
Location estimation for camera navigation is split into the three (3) categories; map-based, map-
building-based and mapless. Map-based consists of providing the database with a model of the
environment in the system. These models may contain different detail degree, varying from a
complete computer-aided design (CAD) model of the environment to a simple graph of
interconnections or interrelationships between the elements in the environment. The technique
can be considered as self-localization and is a fundamental technique for a correct navigation.
The main steps in the technique are: capture image information, detect landmarks in current
views (objects, edges or corner), match observed landmarks with those contained in the
database according to certain criteria, and update the user position, as a function of the matched
landmarks location in the stored map.
Map-building-based is method that provides system capability by exploring the environment
and building its map by itself (see example in Erhard et al, [27] and Goedemé et al, [28]). The
navigation process starts once the system has explored the environment and stored its
representation. Mapless is a method that provides the system in which navigation is achieved
without any prior description of the environment. It is depends on the elements observed in the
user environment such as: walls, features, doors and desks. There are two (2) main navigation
techniques based on mapless: optical-flow and appearance-based navigation. Technique based
on optical-flow is estimate the features or objects motion in the sequence of images. Most of the
researchers develop an optical flow system by using pioneering techniques based on (see in
article Hom et al, [29] and Lucas et al, [30]). While the technique that using appearance-based
is a matching techniques based on the images storage in a previous recording phase. These
images are then used as templates. The system self locates and navigates in the environment to
match the current viewed frame with the stored templates. Outdoor navigation can be
categorized in two (2); structured and unstructured environment. Algorithm color based that
already developed by Rizzi et al, [31], Stanikunas et al, [32], Ebner [33], Foster [34], Ebner
[35], Biancoa et al, [36] and Martínez-Verdú et al, [37], and texture based can be used in ‘road
following method’ in order to recognize the lines of the road or any structured infrastructure and
navigate consistently. For unstructured environment, method such as Wilcox et al, [38] and
Krotkov et al, [39] can be applied since there are no regular properties to solve kind situation
(see detail in Bonin-Font et al, [20]).
7. Signal & Image Processing : An International Journal(SIPIJ) Vol.2, No.1, March 2011
30
3.2.3 GPS Based
In this section, we focus only on location determination by using standalone embedded GPS on
mobile phone in structured environment (ex: road) since it needs integration with other device
or sensor in order to make it survive in unstructured environment. This technique called as map
matching algorithm and it can be subdivided into geometric analysis, topological analysis,
probabilistic map-matching algorithms and advanced map-matching algorithms.
A geometric map-matching algorithm makes use of the geometric information of the spatial
road network data by considering only the shape of the links (see detail in Greenfeld [40]). In
the geometric map-matching algorithm, the technique based on simple search algorithm is most
commonly used. There are three (3) types, which are point-to-point matching, point-to-curve
matching and curve-to-curve matching. Point-to-point matching refers to the matches of each
position fixes to the closest ‘node’ or ‘shape point’ of a road segment. Point-to-curve matching
(see detail in Bernstein et al, [41] and White et al, [42]) refers to the matches of the point (the
position fix obtained from the navigation system) on to the closest curve in the network.
Meanwhile, curve-to-curve matching (see detail in Bernstein et al, [41] and White et al, [42])
compares the vehicle’s trajectory against known roads.
A topological map-matching algorithm is an algorithm that using the links geometry (such as:
points, lines, and polygons) as the links connectivity and contiguity (see example in Greenfeld
[40]).
A probabilistic algorithm is refers to algorithm that requires the information definition of an
elliptical or rectangular confidence region around a position fix which is obtained from a
navigation sensor (such as: GPS). The error region is superimposed on the road network to
identify a road segment. If the error region contains more than one street, this algorithm will
perform a weighted search on the candidate streets.
Advanced map-matching algorithms are referred to as those algorithms that use more refined
concepts such as a Kalman Filter or an Extended Kalman Filter (e.g., Kim et al, [43]),
Dempster-Shafer’s mathematical theory of evidence 2 (e.g., Yang et al, [44]), a flexible state-
space model and a particle filter (e.g., Gustafsson et al, [45]), an interacting multiple model
(e.g., Cui et al, [46]), a fuzzy logic model (e.g., Kim et al, [47] ), or the application of Bayesian
inference (e.g., Pyo et al, [48]).
4. CONCLUSIONS
In the next generation of mobile navigation system, people will need more alternative types of
context information of the environments on the mobile phone, not just only limited to
communication services. One of the information context which is focused in this paper is the
location context in the mobile phone. The usage of location context (ex: GPS) is becoming more
popular nowadays. By utilizing and improving existing location determination techniques, this
will enable location wares to be more intelligence in order to upgrade the quality of life. In this
paper, we presented the taxonomy for location determination on mobile navigation system
which is crucial to the establishment of ubiquitous positioning on mobile phone. The proposed
taxonomy was constructed from a literature study of papers and articles about positioning
estimation. The taxonomy was presented consists of the five taxons as follows: scale, output,
measurements, roles and estimation method. Valuable taxonomies can account for everything
8. Signal & Image Processing : An International Journal(SIPIJ) Vol.2, No.1, March 2011
31
that is known so far and can predict things to come, as variations of parameters accounted for
and enumerated in the taxonomy. The proposed taxonomy was presented shows the depth and
the breadth of our understanding. We would like others to join and based on the inputs from the
community we can further improve the proposed taxonomy.
ACKNOWLEDGEMENTS
This paper was inspired from my master research project which is related to ubiquitous
positioning on mobile phone. The author also would like to thank Mohd Murtadha b Mohamad
for his insightful comments on earlier drafts of this paper.
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Authors
Wan Mohd Yaakob Wan Bejuri received the
Dip. in Electronic Engineering in 2005 from
Politeknik Kuching Sarawak and the B
(Computer Science) from Universiti Teknologi
Malaysia in 2009. He currently M.Sc
at Universiti Teknologi Malaysia.
Mohd Murtadha Mohamad received the
(Computer) from Universiti
Malaysia. He also received Ph.D. (Electrical)
and M.Sc. (Embedded Sys. Eng) from
Watt University. He currently senior lecturer at
Universiti Teknologi Malaysia and also a
member of IEEE. For detail, please go to:
http://csc.fsksm.utm.my/murtadha/
Maimunah Sapri received the Dip. in Estate
Management from Institute of Technology
MARA. She also received B.Surv. (Ho
Property Management and M.Sc. (Facilities
Management) from Universiti Teknologi
Malaysia and reveived Ph.D (Real Estate
Management) from Heriot-Watt University.
currently senior lecturer at Universiti
Malaysia.
Signal & Image Processing : An International Journal(SIPIJ) Vol.2, No.1, March 2011
D. Shin & T. Sung, “Development of a map-matching method using the
IEEE Proceedings on Intelligent Transportation Systems
Wan Mohd Yaakob Wan Bejuri received the
in 2005 from
Sarawak and the B.Sc.
from Universiti Teknologi
Sc. candidate
Mohd Murtadha Mohamad received the B.Eng.
(Computer) from Universiti Teknologi
D. (Electrical)
from Heriot-
currently senior lecturer at
and also a
For detail, please go to:
ri received the Dip. in Estate
Management from Institute of Technology
Surv. (Hons.)
Sc. (Facilities
iti Teknologi
Malaysia and reveived Ph.D (Real Estate
Watt University. She
y senior lecturer at UniversitiTeknologi
Signal & Image Processing : An International Journal(SIPIJ) Vol.2, No.1, March 2011
34
matching method using the multiple
IEEE Proceedings on Intelligent Transportation Systems, pp. 23–27.