Location Aware Computing

Emerging ubiquitous and pervasive computing applications often need to know where things are physically located. To meet this need, many locationsensing systems have been developed, but none of the systems for the indoor environment have been widely adopted. In this paper we propose Proximity Mining, a new approach to build location information by mining sensor data. The Proximity Mining does not use geometric views for location modeling, but automatically discovers symbolic views by mining time series data from sensors which are placed in surroundings. We deal with trend curves representing time series sensor data, and use their topological characteristics to classify locations where the sensors are placed.

The Java Location API for J2ME TM integrates generic positioning and orientation data with persistent storage of landmark objects. It can be used to develop location based service applications for small mobile devices, and these applications can be tested using simulation environments. Currently the only simulation tools in the public domain are proprietary mobile device simulators that are driven by GPS data log files, but it is sometimes useful to be able to test location based services using interactive map-based tools. In addition, we may need to experiment with extensions and changes to the standard API to support additional services, requiring an open source environment. In this paper we describe the implementation of an open source map-based simulation tool compatible with other commonly used development and deployment tools.

NASA's vision for space exploration (February 2004) calls for development of a new crew exploration vehicle, sustained lunar operations, and human exploration of Mars. To meet the challenges of planned sustained operations as well as the limited communications between Earth and the crew (e.g., Mars exploration), many systems will require crews to operate in an autonomous environment. It has been estimated that once every 2.4 years a major medical issue will occur while in space. NASA's future travels, especially to Mars, will begin to push this timeframe. Therefore, now is the time for investigating technologies and systems that will support crews in these environments. Therefore, this summer two studies were conducted to evaluate the technology and systems that may be used by crews in future missions. The first study evaluated three commercial Indoor Positioning Systems (IPS) (Versus, Ekahau, and Radianse) that can track equipment and people within a facility. While similar to Global Positioning Systems (GPS), the specific technology used is different. Several conclusions can be drawn from the evaluation conducted, but in summary it is clear that none of the systems provides a complete solution in meeting the tracking and technology integration requirements of NASA. From a functional performance (e.g., system meets user needs) evaluation perspective, Versus performed fairly well on all performance measures as compared to Ekahau and Radianse. However, the system only provides tracking at the room level. Thus, Versus does not provide the level of fidelity required for tracking assets or people for NASA requirements. From an engineering implementation perspective, Ekahau is far simpler to implement that the other two systems because of its wi-fi design (e.g., no required runs of cable). By looking at these two perspectives, one finds there was no clear system that met NASA requirements. Thus it would be premature to suggest that any of these systems are ready for implementation and further study is required. The second study evaluated current medical packs, used on-board the International Space Station (ISS), in the execution of an emergency medical procedure as compared to a modified design. An experiment using 13 participants found no difference in performance time between the two packs; however, it did find a marginally significant difference (p = 0.08) in the number of errors with the modified design resulting in less errors. Using the experimental data collected, a computer model was developed that allowed for running larger sample sizes. Results from this model found a statistically significant differences for time and errors (p<0.05). Further modeling evaluated the effect of errors on performance time. Results once again found a statistically significant difference for time and found that the current pack design's performance in time was 4 times greater when errors were considered as compared to the design when errors were ignored. However, the modified pack only saw a 2 times increase when errors were considered. Given that NASA typically is dealing with small samples and limited resources to test participants, modeling should be considered to evaluate designs prior to experimentation. Future work will investigate the value in developing a desktop application for modeling medical procedures independent of experimentation. This modeling does not preclude experimental efforts, but it does provide guidance in conducting experiments. Both studies highlight issues that require further investigation. These studies are just one step needed to prepare systems and technologies for future planned human exploration.

The UCSD ActiveCampus project is an exploration of wireless location-aware computing in the university setting. ActiveClass supports classroom activities such as anonymous asking of questions, polling, and student feedback. ActiveCampus Explorer supports several location aware applications, including location-aware instant messaging and maps of the user's location annotated with dynamic hyperlinks of nearby buddies, digital graffiti, etc. This paper describes results on the use of these systems by several hundred students, drawing on observations, aggregate usage data, anecdotes, and the analytical perspective of Ecologies. Analysis exposes novel behaviors, the relevance of proximity in social computing, and a willingness to share location information with others.

Location-aware computing involves the automatic tailoring of information and services based on the current location of the user. We have designed and implemented Rover, a system that enables location-based services, as well as the traditional time-aware, user-aware and device-aware services. To achieve system scalability to very large client sets, Rover servers are implemented in an "action-based" concurrent software architecture that enables fine-grained application-specific scheduling of tasks. We have demonstrated feasability through implementations for both outdoor and indoor environments on multiple platforms.

Abstract-The variety in wireless technology and mobile computing devices has caused a growing application of location-sensing systems and correspondence services. The indoor location sensing system which applies radio frequency identification technology (RFID) is the most popular research topic in the area of location-sensing systems, and LANDMARC is the most representative one. However, LANDMARC suffers the drawback of inaccuracy in unstable signal intensity. A Virtual Signal Location System (VSLS) is designed and developed to overcome some drawbacks of LANDMARC. The concept of VSLS is based on additional setting of virtual signal tags as well as the normal distribution of signal strength, analysis of sampling rate and equalization to decrease signal intensity error. Comparisons were made with LANDMARC; these showed that VSLS effectively increased the sampling quality of the signal as well as the precision of positioning.

Emerging ubiquitous and pervasive computing applications often need to know where things are physically located. To meet this need, many locationsensing systems have been developed, but none of the systems for the indoor environment have been widely adopted. In this paper we propose Proximity Mining, a new approach to build location information by mining sensor data. The Proximity Mining does not use geometric views for location modeling, but automatically discovers symbolic views by mining time series data from sensors which are placed in surroundings. We deal with trend curves representing time series sensor data, and use their topological characteristics to classify locations where the sensors are placed.

Policy enforcement is an integral part of many applications. Policies are often used to control access to sensitive information. Current policy specification languages give users fine-grained control over when and how information can be accessed, and are flexible enough to be used in a variety of applications. Evaluation of these policies, however, is not optimized for performance. Emerging applications, such as real-time enforcement of privacy policies in a sensor network or location-aware computing environment, require high throughput. Our experiments indicate that current policy enforcement solutions are unable to deliver the level of performance needed for such systems, and limit their overall scalability. To deal with the need for high-throughput evaluation, we propose CPOL, a flexible C++ framework for policy evaluation. CPOL is designed to evaluate policies as efficiently as possible, and still maintain a level of expressiveness comparable to current policy languages. CPOL achieves its performance goals by efficiently evaluating policies and caching query results (while still preserving correctness). To evaluate CPOL, we ran a simulated workload of users making privacy queries in a location-sensing infrastructure. CPOL was able to handle policy evaluation requests two to six orders of magnitude faster than a MySql implementation and an existing policy evaluation system. We present the design and implementation of CPOL, a high-performance policy evaluation engine, along with our testing methodology and experimental results.

Location systems have several demanding applications par- ticularly in indoor environments but require costly infrastructure of sen- sors. Received Signal Strength based positioning provides economical viability to enabling these applications. Although extensive research has been carried out in this area still tedious implementation and lengthy de- velopment life cycle prohibit wide scale adoption of this technology. We present a new approach based on Fuzzy ArtTMap neural network that signiflcantly reduces development time. Besides shortening development time of location systems this approach shows competitive accuracy and allows dynamic expansion of location aware site.

This paper focuses on the possibilities of utilising infrastructural RFIDs for location aware computing. A key to automated computer-aided work is location and situation awareness. This allows the system to operate independently from direct user input, minimising the impact on the original process. For demonstration purposes, a large area tracking system using existing RFID technology and infrastructure is developed and evaluated. As a first possible application, we embed the system into an aircraft cabin. The localisation procedure is based on the coordinates of the RFID transponders detected by the RFID reader, as well as the orientation information measured by a gyroscope. To increased robustness concerning environmental noise and interferences, we estimate a tags readability using modulated power output of the antenna. The average error of our demonstration setup is below half a meter. Possible use cases range from maintenance assistance to way finding in commercial shops or underground parking lots.

This paper focuses on the possibilities of utilizing infrastructural RFIDs for location aware computing. A key to automated computer aided work is location and situation awareness. This allows the system to operate independently from direct user input, minimizing the impact on the original process. For demonstration purposes a large area tracking system using existing RFID technology and infrastructure is developed and evaluated. As a first possible application we embed the system into an aircraft cabin. The localization procedure is based on the coordinates of the RFID transponders detected by the RFID reader, as well as the orientation information measured by a gyroscope. Position estimation is accomplished through an iterative algorithm, optimizing the position of the antenna's readability field with respect to the currently visible tags. The average error is below half a meter. Possible use cases range from maintenance assistance to way finding in commercial shops or underground parking lots.

This paper focuses on the possibilities of utilizing infrastructural RFIDs for location aware computing. A key to automated computer aided work is location and situation awareness. This allows the system to operate independently from direct user input, minimizing the impact on the original process. For demonstration purposes a large area tracking system using existing RFID technology and infrastructure is developed and evaluated. As a first possible application we embed the system into an aircraft cabin. The localization procedure is based on the coordinates of the RFID transponders detected by the RFID reader, as well as the orientation information measured by a gyroscope. Position estimation is accomplished through an iterative algorithm, optimizing the position of the antenna's readability field with respect to the currently visible tags. The average error is below half a meter. Possible use cases range from maintenance assistance to way finding in commercial shops or underground parking lots.

This paper focuses on the possibilities of utilising infrastructural RFIDs for location aware computing. A key to automated computer-aided work is location and situation awareness. This allows the system to operate independently from direct user input, minimising the impact on the original process. For demonstration purposes, a large area tracking system using existing RFID technology and infrastructure is developed and evaluated. As a first possible application, we embed the system into an aircraft cabin. The localisation procedure is based on the coordinates of the RFID transponders detected by the RFID reader, as well as the orientation information measured by a gyroscope. To increased robustness concerning environmental noise and interferences, we estimate a tags readability using modulated power output of the antenna. The average error of our demonstration setup is below half a meter. Possible use cases range from maintenance assistance to way finding in commercial shops or underground parking lots.

This paper describes the opportunities for location aware computing to enhance information capture and use within the construction industry. The construction industry is characterized as being slow to take up innovative mobile ICT, despite the highly mobile workforce who must collaborate with a range of on and off-site personnel, and make use of large volumes of information. Based on fieldwork and workshop activities within COMIT (a large-scale mobile IT project within the construction industry), the information used within two key business processes-health and safety audits, and site design problem resolution-is outlined, and the opportunities for support by location aware computing discussed. Some potential challenges are also identified, as is the need to understand how to provide real value (as opposed to just information) to the end user.

In this paper we introduce Location Estimation through Proximity Information (LEPI), an algorithm that aims at locating portable RFID readers in areas where active-RFID grids are settled. Location estimation is accomplished through a proximity information, which the reader derives by performing tag interrogation at increasing RF power levels. RFID tags surrounding the reader are incrementally detected and their known positions are eventually averaged, this providing an accurate estimation of the reader location. The performance of the proposed approach is assessed by experimental trials, conducted in indoor environments. They testify both to the actual feasibility of such a solution and to its better accuracy when compared to other reference RFID-based location techniques.

The ANU department of Computer Science has provided me with a great atmosphere for my PhD research for the past three years. It has been a great privilege to be surrounded by so many excellent computer scientists, both theoretical and experimental, particularly under the supervision of Assoc. Prof. Chris Johnson who brought me to the research and community of Smart Internet Technology. Discussion with him has been a time of great privilege for me and seemingly endless enthusiasm and imagination generated new perspectives: his honest critiques came in the form of deep and inevitably challenging questioning. He is my mentor whose approach is defined by the words of Glaser (1995), who said: "Grab one corner of the problem and go! Start doing it". For such a rich and overwhelming introduction to the world of research I am deeply grateful. I am also grateful for my advisory panel who gave me a lot of invaluable feedback, i.e., Assoc. Prof. Bob Kummerfeld from the University of Sydney and Dr. Ken Taylor from the Commonwealth Scientific and Industrial Research Organisation (CSIRO). I would like to thanks Prof. Matthew James, as the Head of the Department of Engineering (2001-2002), who supported me at the beginning of my study by allowing me to continue working part time as a computer system administrator in the Department while I pursued my studies and for providing me with a fee-waiver scholarship from March 2002-Oct 2002; Prof. Michael Cardew-Hall, as the Head of the Department of Engineering (2002-present) who continuously supported me during my studies and Rob Gresham my supervisor in the Department of Engineering who is very supportive and understanding, he did everything he could to make sure it would be easier for me to do my job. The community in which I have worked throughout this PhD has been extremely generous, both with knowledge and money, i.e., Smart Internet Technology-CRC (http://www.smartinternet.com.au), especially Prof. Darrell Williamson as CEO of SIT-CRC, has provided me with financial support for my PhD from January 2003 to June 2005 (2.5 years) and give me the opportunity to participate in a series of SIT-CRC conferences and to publish my work. Faculty of Engineering and Information Technology (FEIT)-ANU, through the Faculty Grant Research Scheme (FRGS), that provided me with a one year grant for research support (January-December 2004) ANU National Institute of Engineering and Information Sciences (NIEIS) through its NIEIS travel award has provided me with travel support for a conference (January 2004). Department of Computer Science, especially Assoc. Prof. Chris Johnson as its Head of Department, and Department of Engineering, both have provided me with varying financial support, especially travel support to conferences. I also would like to thank several people especially Dr. Eric McCreath and Prof. John Lloyd for valuable discussions in the area of machine learning, several SIT-CRC PhD scholars especially

Advances in location-enhanced technology are making it easier for us to be located by others. These new technologies present a difficult privacy tradeoff, as disclosing one's location to another person or service could be risky, yet valuable. To explore whether and what users are willing to disclose about their location to social relations, we conducted a three-phased formative study. Our results show that the most important factors were who was requesting, why the requester wanted the participant's location, and what level of detail would be most useful to the requester. After determining these, participants were typically willing to disclose either the most useful detail or nothing about their location. From our findings, we reflect on the decision process for location disclosure. With these results, we hope to influence the design of future locationenhanced applications and services.

Growing convergence among mobile computing devices and embedded technology sparks the development and deployment of "context-aware" applications, where location is the most essential context. In this paper we present LANDMARC, a location sensing prototype system that uses Radio Frequency Identification (RFID) technology for locating objects inside buildings. The major advantage of LANDMARC is that it improves the overall accuracy of locating objects by utilizing the concept of reference tags. Based on experimental analysis, we demonstrate that active RFID is a viable and cost-effective candidate for indoor location sensing. Although RFID is not designed for indoor location sensing, we point out three major features that should be added to make RFID technologies competitive in this new and growing market.

Location systems have several demanding applications par- ticularly in indoor environments but require costly infrastructure of sen- sors. Received Signal Strength based positioning provides economical viability to enabling these applications. Although extensive research has been carried out in this area still tedious implementation and lengthy de- velopment life cycle prohibit wide scale adoption of this technology. We present a new approach based on Fuzzy ArtTMap neural network that signiflcantly reduces development time. Besides shortening development time of location systems this approach shows competitive accuracy and allows dynamic expansion of location aware site.

Over last years, Indoor Positioning and Navigation Systems (IPNS) has been subject of intense study and research ought to it has become a blind spot with regard to Positioning and Navigation Software. None of proposed indoor solutions has been as successful as outdoor systems like Global Position System (GPS). Our proposal presents the design and implementation on mobile device(the most common), of a 3D positioning and navigation system for indoor based on the use of Bluetooth (BT) radio technology and implemented using Java and J2ME, this implementation is adaptable to whatever indoor environment (commercial centers, offices, museums, etc.) previously modeled and loaded. This 3D model can be build using the most common 3D design tools with M3G formats support. Location is implemented on BT with distributed estimation (the mobile device performs it).

The growing popularity and use of the radio frequency (RF) in different applications, predominantly in the area of identification and location aware system, has driven many researchers. Versatile qualities, easy availability and simplicity of use have led a spate of development of different systems and technologies based on radio frequency identification (RFID). This paper is an attempt to survey the

With mobile telephony and GPS devices becoming ubiquitous, there are many tracking and monitoring devices being developed that have a range of potential applications, from supporting mobile learning to remote health monitoring of the elderly and chronically ill. However, do users actually understand how much of their personal information is being shared with others? In general, there will be a trade off between usefulness of disclosing private information and the risk of it being misused. In this position paper, we describe the ...

Over last years, Indoor Positioning and Navigation Systems (IPNS) has been subject of intense study and research ought to it has become a blind spot with regard to Positioning and Navigation Software. None of proposed indoor solutions has been as successful as outdoor systems like Global Position System (GPS). Our proposal presents the design and implementation on mobile device(the most common), of a 3D positioning and navigation system for indoor based on the use of Bluetooth (BT) radio technology and implemented using Java and J2ME, this implementation is adaptable to whatever indoor environment (commercial centers, offices, museums, etc.) previously modeled and loaded. This 3D model can be build using the most common 3D design tools with M3G formats support. Location is implemented on BT with distributed estimation (the mobile device performs it).

Over last years, Indoor Positioning and Navigation Systems (IPNS) has been subject of intense study and research ought to it has become a blind spot with regard to Positioning and Navigation Software. None of proposed indoor solutions has been as successful as outdoor systems like Global Position System (GPS). Our proposal presents the design and implementation on mobile device(the most common), of a 3D positioning and navigation system for indoor based on the use of Bluetooth (BT) radio technology and implemented using Java and J2ME, this implementation is adaptable to whatever indoor environment (commercial centers, offices, museums, etc.) previously modeled and loaded. This 3D model can be build using the most common 3D design tools with M3G formats support. Location is implemented on BT with distributed estimation (the mobile device performs it).

This paper provides the research background and system approach for project BlueStar. Our aim is to develop a system using a flexible in/outdoor location management scheme that allows for only the end-user to be aware of their location, while still enabling them to access location-relevant information from a centralised source. In such a system the user can choose the level of granularity with which they provide or publish their location details in contrast to systems in which a fixed network is used to track the user. BlueStar addresses the need for a scalable user-centric end-to-end solution in which enduser privacy is protected. As we show in this paper many existing indoor tracking systems rely on special purpose receivers (badges) and transmitters in conjunction with a costly site radio survey, neither of which is necessary in the BlueStar model. Finally, this paper describes one possible location-aware peerto-peer application, using location sniffing, namely an "ad-hocracy".

Over last years, Indoor Positioning and Navigation Systems (IPNS) has been subject of intense study and research ought to it has become a blind spot with regard to Positioning and Navigation Software. None of proposed indoor solutions has been as successful as outdoor systems like Global Position System (GPS). Our proposal presents the design and implementation on mobile device(the most common), of a 3D positioning and navigation system for indoor based on the use of Bluetooth (BT) radio technology and implemented using Java and J2ME, this implementation is adaptable to whatever indoor environment (commercial centers, offices, museums, etc.) previously modeled and loaded. This 3D model can be build using the most common 3D design tools with M3G formats support. Location is implemented on BT with distributed estimation (the mobile device performs it).

Location systems have several demanding applications par- ticularly in indoor environments but require costly infrastructure of sen- sors. Received Signal Strength based positioning provides economical viability to enabling these applications. Although extensive research has been carried out in this area still tedious implementation and lengthy de- velopment life cycle prohibit wide scale adoption of this technology. We present a new approach based on Fuzzy ArtTMap neural network that signiflcantly reduces development time. Besides shortening development time of location systems this approach shows competitive accuracy and allows dynamic expansion of location aware site.

The UCSD ActiveCampus project is an exploration of wireless location-aware computing in the university setting. ActiveClass supports classroom activities such as anonymous asking of questions, polling, and student feedback. ActiveCampus Explorer supports several location aware applications, including location-aware instant messaging and maps of the user's location annotated with dynamic hyperlinks of nearby buddies, digital graffiti, etc. This paper describes results on the use of these systems by several hundred students, drawing on observations, aggregate usage data, anecdotes, and the analytical perspective of Ecologies. Analysis exposes novel behaviors, the relevance of proximity in social computing, and a willingness to share location information with others.

The growing popularity and use of the radio frequency (RF) in different applications, predominantly in the area of identification and location aware system, has driven many researchers. Versatile qualities, easy availability and simplicity of use have led a spate of development of different systems and technologies based on radio frequency identification (RFID). This paper is an attempt to survey the

The increase in utilisation of mobile location-based services for commercial, safety and security purposes among others are the key drivers for improving location estimation accuracy to better serve those purposes. This paper proposes the application of Levenberg Marquardt training algorithm on new robust multilayered perceptron neural network architecture for mobile positioning fitting for the urban area in the considered GSM network using received signal strength (RSS). The key performance metrics such as accuracy, cost, reliability and coverage are the major points considered in this paper. The technique was evaluated using real data from field measurement and the results obtained proved the proposed model provides a practical positioning that meet Federal Communication Commission (FCC) accuracy requirement.

Growing convergence among mobile computing devices and embedded technology sparks the development and deployment of "context-aware" applications, where location is the most essential context. In this paper we present LANDMARC, a location sensing prototype system that uses Radio Frequency Identification (RFID) technology for locating objects inside buildings. The major advantage of LANDMARC is that it improves the overall accuracy of locating objects by utilizing the concept of reference tags. Based on experimental analysis, we demonstrate that active RFID is a viable and cost-effective candidate for indoor location sensing. Although RFID is not designed for indoor location sensing, we point out three major features that should be added to make RFID technologies competitive in this new and growing market.

Safeguarding location privacy is becoming a critical issue in locationbased services and location-aware computing generally. Two drawbacks of many previous models of location privacy are: 1) the models only consider a person's location privacy protection, but not the invasion of location privacy by external agents; and 2) the models are static and do not consider the spatiotemporal aspects of movement. We argue that, to be complete, any model of location privacy needs to enable the analysis and identification of techniques both to protect and to invade an individual's location privacy over time. One way to protect an individual's location privacy is to minimize the information revealed about a person's location, termed obfuscation. This paper presents an explicitly spatiotemporal model of location privacy that models a third party's limited knowledge of a mobile individual's location. We identify two core strategies that a third party can use to refine its knowledge, so potentially invading that mobile individual's location privacy. A global refinement strategy uses the entire history of knowledge about an agent's location in a single step. A local refinement strategy iteratively constructs refined knowledge over time. We present a formal model of global and local refinement operators, and show how this formal model can be translated into a computational model in a simulation environment.

Abstract: This paper offers a critique of Hewlett-Packard&#x27;s &#x27;Cooltown&#x27;, a web-based vision of a near future organized according to the logic of ubiquitous mobile technologies. We argue that Cooltown is prototypical of 1. utopian corporate discourses that frame mobile ...

Over last years, Indoor Positioning and Navigation Systems (IPNS) has been subject of intense study and research ought to it has become a blind spot with regard to Positioning and Navigation Software. None of proposed indoor solutions has been as successful as outdoor systems like Global Position System (GPS). Our proposal presents the design and implementation on mobile device(the most common), of a 3D positioning and navigation system for indoor based on the use of Bluetooth (BT) radio technology and implemented using Java and J2ME, this implementation is adaptable to whatever indoor environment (commercial centers, offices, museums, etc.) previously modeled and loaded. This 3D model can be build using the most common 3D design tools with M3G formats support. Location is implemented on BT with distributed estimation (the mobile device performs it).

Sentient Computing provides computers with perception so that they can react and provide assistance to user activities. Physical spaces are made sentient when they are wired with networks of sensors capturing context data, which is communicated to computing devices spread through the environment. These devices interpret the information provided and react by performing the actions expected by the user. Among the types of context information provided by sensors, location has proven to be especially useful. Since location is an important context that changes whenever the user moves, a reliable location-tracking system is critical to many sentient applications. However, the sensor technologies used in indoor location tracking are expensive and complex to deploy, configure and maintain. These factors have prevented a wider adoption of Sentient Computing in our living and working spaces. This paper presents TRIP, a low-cost and easily deployable vision-based sensor technology addressing these issues. TRIP employs off-the-shelf hardware (lowcost CCD cameras and PCs) and printable 2-D circular markers for entity identification and location. The usability of TRIP is illustrated through the implementation of several sentient applications.

An important aspect of the growing e-commerce sector involves the delivery of tangible goods to the end customer, the so-called last mile. This final stage of the logistics chain remains highly inefficient due to the problem of failed deliveries. To address this problem, delivery service providers can apply data science to determine the optimal, customer-centered location and time window for handover. In this paper, we present a three-step approach for location prediction, based on mobile location data, in order to support delivery planning. The first step is identifying a user's locations of interest through density-based clustering. Next, the semantics (home or work) of the user's locations of interest are discovered, based on temporal assumptions. Finally, we predict future locations with a decision tree model that is trained on each user's historical location data. Though the problem of location prediction is not new, this work is the first to apply it to the field of parcel delivery with its corresponding implications. Moreover, we provide a novel and detailed evaluation on real-world data from a parcel delivery service. The promising results indicate that our approach has the potential to help delivery service providers to gain insights into their customers' optimal delivery time and location in order to support delivery planning. Eventually this will decrease last-mile delivery costs and boost customer satisfaction.

Over last years, Indoor Positioning and Navigation Systems (IPNS) has been subject of intense study and research ought to it has become a blind spot with regard to Positioning and Navigation Software. None of proposed indoor solutions has been as successful as outdoor systems like Global Position System (GPS). Our proposal presents the design and implementation on mobile device(the most common), of a 3D positioning and navigation system for indoor based on the use of Bluetooth (BT) radio technology and implemented using Java and J2ME, this implementation is adaptable to whatever indoor environment (commercial centers, offices, museums, etc.) previously modeled and loaded. This 3D model can be build using the most common 3D design tools with M3G formats support. Location is implemented on BT with distributed estimation (the mobile device performs it).

In this paper, we present a new method for camera calibration using concentric circles. We demonstrate that camera calibration is possible using two views of a concentric circle with known size. A new method to determine the position of the projected center of the circle is introduced. Based on the accurate estimation of the projected circle center of two sets of 3-D concentric circles, the proposed calibration method estimates the intrinsic camera parameters using two sets of 3-D concentric circles obtained from the same viewpoint. We validate the performance of the method using both synthetic and real images. Our method shows a comparable performance with respect to similar calibration methods using a plane. The use of concentric circles, however, greatly simplifies the calibration problem. We also demonstrate the feasibility of the proposed calibration method through the recovery of 3-D structure of an object, placed on a turntable, using a sequence of images taken from the static cameras.

Over last years, Indoor Positioning and Navigation Systems (IPNS) has been subject of intense study and research ought to it has become a blind spot with regard to Positioning and Navigation Software. None of proposed indoor solutions has been as successful as outdoor systems like Global Position System (GPS). Our proposal presents the design and implementation on mobile device(the most common), of a 3D positioning and navigation system for indoor based on the use of Bluetooth (BT) radio technology and implemented using Java and J2ME, this implementation is adaptable to whatever indoor environment (commercial centers, offices, museums, etc.) previously modeled and loaded. This 3D model can be build using the most common 3D design tools with M3G formats support. Location is implemented on BT with distributed estimation (the mobile device performs it).

Location-aware computing is regarded as a key feature of many future mobile applications. GPS serves well for most outdoor applications; however, its dependence on satellites makes it ineffective in indoor environments. Several technologies such as infrared sensing, radio frequency, ultrasonic and RFIDs have been proposed for indoor location sensing. Each of these methods has its own merits and shortcomings. Recently there has been an increase in the use of commodity wireless technologies like 802.11 or Bluetooth for indoor location positioning. Since BT and WLAN don't get along very well, the paper presents experimental results of interference effect of one technology on the other. These results help in determining which of these two technologies is more suitable for location sensing applications. The paper also presents two techniques of how Bluetooth technology can be used (with and without the use of signal strength information) for location sensing. The paper concludes by suggesting some changes to the Bluetooth architecture to improve its capabilities for location positioning. 3.1 Influence of 802.11b devices on other 802.11b devices Case A-1: Single pair of 802.11b devices present in the environment-No Interference An iPAQ with D-Link card and a laptop with Orinoco card are configured to ping each other over the same channel (Channel 6). The activities of a particular

Emerging ubiquitous and pervasive computing applications often need to know where things are physically located. To meet this need, many locationsensing systems have been developed, but none of the systems for the indoor environment have been widely adopted. In this paper we propose Proximity Mining, a new approach to build location information by mining sensor data. The Proximity Mining does not use geometric views for location modeling, but automatically discovers symbolic views by mining time series data from sensors which are placed in surroundings. We deal with trend curves representing time series sensor data, and use their topological characteristics to classify locations where the sensors are placed.

With mobile telephony and GPS devices becoming ubiquitous, there are many tracking and monitoring devices being developed that have a range of potential applications, from supporting mobile learning to remote health monitoring of the elderly and chronically ill. However, do users actually understand how much of their personal information is being shared with others? In general, there will be a trade off between usefulness of disclosing private information and the risk of it being misused. In this position paper, we describe the ...