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The purpose of this paper is to establish an application platform that addresses expensive development cost and effort of indoor location-aware application (InL-Apps) problems caused by tightly coupling between InL-App and indoor positioning systems (IPSs).

To achieve this purpose, in this paper, the authors proposes a Web-based integration framework called Web-based Integration Framework for Indoor Location (WIF4InL). With a common data model, WIF4InL integrates indoor location data obtained from heterogeneous IPS. It then provides application-neutral application programming interface (API) for various InL-Apps.

The authors integrate two different IPS (RedPin and BluePin) using WIF4InL and conduct a comparative study which is based on sufficiency of essential capabilities of location-dependent queries among three systems: RedPin, BluePin and WIF4InL. WIF4InL supports more capabilities for the location-dependent queries. Through the data and operation integration, WIF4InL even enriches the existing proprietary IPS.

As WIF4InL allows the loose coupling between IPS and InL-Apps, it significantly improves reusability of indoor location information and operation.

With the rapid development of the indoor spaces positioning technologies such as the radio-frequency identification (RFID), Bluetooth and WI-FI, the locations of indoor spatial objects (static or moving) constitute an important foundation for a variety of applications. However, there are many challenges and limitations associated with the structuring and querying of spatial objects in indoor spaces. The purpose of this study is to address the current trends, limitations and future challenges associated with the structuring and querying of spatial objects in indoor spaces. Also it addresses the related features of indoor spaces such as indoor structures, positioning technologies and others.

In this paper, the author focuses on understanding the aspects and challenges of spatial database managements in indoor spaces. The author explains the differences between indoor spaces and outdoor spaces. Also examines the issues pertaining to indoor spaces positioning and the impact of different shapes and structures within these spaces. In addition, the author considers the varieties of spatial queries that relate specifically to indoor spaces.

Most of the research on data management in indoor spaces does not consider the issues and the challenges associated with indoor positioning such as the overlapping of Wi-Fi. The future trend of the indoor spaces includes included different shapes of indoors beside the current 2D indoor spaces on which the majority of the data structures and query processing for spatial objects have focused on. The diversities of the indoor environments features such as directed floors, multi-floors cases should be considered and studied. Furthermore, indoor environments include many special queries besides the common ones queries that used in outdoor spaces such as KNN, range and temporal queries. These special queries need to be considered in data management and querying of indoor environments.

To the best of the author’s knowledge, this paper successfully addresses the current trends, limitations and future challenges associated with the structuring and querying of spatial objects in indoor spaces.

Location awareness is essential to decisions pertinent to tracking and progress reporting, as well as to safety in construction projects. However, these applications have been mostly limited to the outdoor environment, where satellites for positioning information are in view. Recent studies on indoor location sensing systems are now overcoming this limitation and offering significant potential on construction practices, and radio frequency identification (RFID) is the most widely utilised technology for such application. The purpose of this paper is to address a wide range of protocols that are vital for RFID deployment for indoor construction. The paper identifies deployment settings to provide data acquisition with higher accuracy for indoor location sensing in construction.

A computational platform was designed to assess and evaluate the most suitable condition related to deployment of reference tags in construction. In this platform, a number of protocols and parameters are presented and their performance is evaluated. The evaluation scenarios were performed on a construction facility in Montreal, as well as in a controlled lab environment. The computational platform used for the study comprises the use of passive reference RFID tags and K Nearest Neighbour algorithm (K‐NN) for course‐grained detection of target's location and its classification into pre‐defined zone areas.

The studies resulted in a number of observations, findings, and lessons learned for RFID deployment in construction. The results indicate that: the speed of the reader is in direct relationship with the detection error rate; zone configuration effectiveness is in direct relationship with the deployed RFID read‐range; error rate on the controlled environment is significantly lower than rates in construction site; and stationary reader performs better than moving reader.

The paper's findings are expected to be of considerable value to researchers and practitioners involved in the utilisation of RFID technology in construction. The paper provides a set of helpful protocols for the deployment of passive RFIDs for automated onsite management of construction operations.

Window shading has always been an effective technique to control the access of solar radiation; however, inappropriate selection of the shading technique, location and optical properties may lead to an increase in energy consumed for cooling and artificial lighting. Venetian blinds (VBs) are a type of adjustable shading devices that can be installed to the interior, exterior or in between glass panes of a window and that can be easily implemented in both new and existing buildings. This study aims to investigate the impact of three VB parameters: slat angle, reflectivity and location on the overall energy consumption of a residential space with a south-facing facade under the hot arid desert climate of Saudi Arabia’s capital, Riyadh. For the purpose of globalizing the findings, the same investigations were applied for two other cities of similar climates: Cairo, Egypt, and Arizona, the USA.

A test room was modelled for energy simulation, with a 20% window-to-wall ratio. A VB was assigned with alternatives of being located to the indoor, outdoor or in between double glass panes. High, medium and low reflectivity values were applied at each location at slat angle alternatives of 15°, 30°, 45°, 60°, 75° and 90°.

Results showed VB performance across slat angles, where up to 20.1% energy savings were achieved by mid-pane high reflectivity VBs in Riyadh, while the value exceeded 30% in case of being externally located. A similar performance pattern occurred in the other two cities of hot arid desert climates: Cairo and Arizona.

The study is limited to VBs at a fixed position, with no upward movement for partial or full openness conditions. The effect of blind control and operation on performance, such as the amount and duration of openness/closure of the blind and changes in slat angle across time, in addition to VB automation, shall be investigated in a future study.

The better understanding of VB energy performance achieved would enhance a more rational selection of VBs, which would benefit the construction industry as it would assist designers, real estate developer companies, as well as end-users in the decision-making process and help to realize energy-efficient solutions in residential buildings. VB production entities would also benefit by manufacturing and promoting for energy-efficient products.

In this study, a matrix of combinations of three VB parameters was developed, and the effect of these combinations on the overall energy consumption of both artificial lighting and heating, ventilation and air conditioning (HVAC) systems was evaluated and compared to identify the combinations of higher efficiency. The literature showed that these three parameters were hardly investigated in a combined form and hardly assessed by considering the overall energy consumed by both artificial lighting and HVAC.

The purpose of this study is to use visual and inertial sensors to achieve real-time location. How to provide an accurate location has become a popular research topic in the field of indoor navigation. Although the complementarity of vision and inertia has been widely applied in indoor navigation, many problems remain, such as inertial sensor deviation calibration, unsynchronized visual and inertial data acquisition and large amount of stored data.

First, this study demonstrates that the vanishing point (VP) evaluation function improves the precision of extraction, and the nearest ground corner point (NGCP) of the adjacent frame is estimated by pre-integrating the inertial sensor. The Sequential Similarity Detection Algorithm (SSDA) and Random Sample Consensus (RANSAC) algorithms are adopted to accurately match the adjacent NGCP in the estimated region of interest. Second, the model of visual pose is established by using the parameters of the camera itself, VP and NGCP. The model of inertial pose is established by pre-integrating. Third, location is calculated by fusing the model of vision and inertia.

In this paper, a novel method is proposed to fuse visual and inertial sensor to locate indoor environment. The authors describe the building of an embedded hardware platform to the best of their knowledge and compare the result with a mature method and POSAV310.

This paper proposes a VP evaluation function that is used to extract the most advantages in the intersection of a plurality of parallel lines. To improve the extraction speed of adjacent frame, the authors first proposed fusing the NGCP of the current frame and the calibrated pre-integration to estimate the NGCP of the next frame. The visual pose model was established using extinction VP and NGCP, calibration of inertial sensor. This theory offers the linear processing equation of gyroscope and accelerometer by the model of visual and inertial pose.

The purpose of this paper is to develop a mobile service, based on anonymous location-based data, to help students find available reading rooms on a university campus. To evaluate this mobile service, both a usability test and a technology acceptance test were carried out.

The research followed a design science approach, including developing a prototype and evaluating the developed prototype.

The results from the usability test indicated good usability of the developed mobile service. The results from the technology acceptance test demonstrated students’ intention to use this mobile service. Most respondents indicated that they would like to use this mobile service to find available reading rooms when they are on campus.

The results imply that there are other contexts where anonymous location-based data are also useful. A similar mobile service can be developed for other contexts, such as, hospital complexes, shopping malls, and airports.

To the authors best knowledge, the authors have not found any mobile services aiming at counting the density of people residing in a room by using anonymous user location-based data on a university campus. This research fills this gap by developing the mobile service, called finding reading rooms.

The purpose of this paper is to develop a facade for seamlessly using locating services and enabling easy development of an application with indoor and outdoor location information without being aware of the difference of individual services. To achieve this purpose, in this paper, a unified locating service, called KULOCS (Kobe-University Unified LOCating Service), which horizontally integrates the heterogeneous locating services, is proposed.

By focusing on technology-independent elements [when], [where] and [who] in location queries, KULOCS integrates data and operations of the existing locating services. In the data integration, a method where the time representation, the locations and the namespace are consolidated by the Unix time, the location labels and the alias table, respectively, is proposed. Based on the possible combinations of the three elements, an application-neutral application programming interface (API) for the operation integration is derived.

Using KULOCS, various practical services are enabled. In addition, the experimental evaluation shows the practical feasibility by comparing cases with or without KULOCS. The result shows that KULOCS reduces the effort of application development, especially when the number of locating services becomes large.

KULOCS works as a seamless facade with the underlying locating services, the users and applications consume location information easily and efficiently, without knowing concrete services actually locating target objects.

This study aims to design a new low-cost localization platform for estimating the location and orientation of a pedestrian in a building. The micro-electro-mechanical systems (MEMS) sensor error compensation and the algorithm were improved to realize the localization and altitude accuracy.

The platform hardware was designed with common low-performance and inexpensive MEMS sensors, and with a barometric altimeter employed to augment altitude measurement. The inertial navigation system (INS) – extended Kalman filter (EKF) – zero-velocity updating (ZUPT) (INS-EKF-ZUPT [IEZ])-extended methods and pedestrian dead reckoning (PDR) (IEZ + PDR) algorithm were modified and improved with altitude determined by acceleration integration height and pressure altitude. The “AND” logic with acceleration and angular rate data were presented to update the stance phases.

The new platform was tested in real three-dimensional (3D) in-building scenarios, achieved with position errors below 0.5 m for 50-m-long route in corridor and below 0.1 m on stairs. The algorithm is robust enough for both the walking motion and the fast dynamic motion.

The paper presents a new self-developed, integrated platform. The IEZ-extended methods, the modified PDR (IEZ + PDR) algorithm and “AND” logic with acceleration and angular rate data can improve the high localization and altitude accuracy. It is a great support for the increasing 3D location demand in indoor cases for universal application with ordinary sensors.

Pervasive computing environments such as a pervasive campus domain, shopping, etc. will become commonplaces in the near future. The key to enhance these system environments with services relies on the ability to effectively model and represent contextual information, as well as spontaneity in downloading and executing the service interface on a mobile device. The system needs to provide an infrastructure that handles the interaction between a client device that requests a service and a server which responds to the client's request via Web service calls. The system should relieve end‐users from low‐level tasks of matching services with locations or other context information. The mobile users do not need to know or have any knowledge of where the service resides, how to call a service, what the service API detail is and how to execute a service once downloaded. All these low‐level tasks can be handled implicitly by a system. The aim of this paper is to investigate the notion of context‐aware regulated services, and how they should be designed, and implemented.

The paper presents a detailed design, and prototype implementation of the system, called mobile hanging services (MHS), that provides the ability to execute mobile code (service application) on demand and control entities' behaviours in accessing services in pervasive computing environments. Extensive evaluation of this prototype is also provided.

The framework presented in this paper enables a novel contextual services infrastructure that allows services to be described at a high level of abstraction and to be regulated by contextual policies. This contextual policy governs the visibility and execution of contextual services in the environment. In addition, a range of contextual services is developed to illustrate different types of services used in the framework.

The main contribution of this paper is a high‐level model of a system for context‐aware regulated services, which consists of environments (domains and spaces), contextual software components, entities and computing devices.

Buildings use approximately 40% of global energy and are responsible for almost a third of the worldwide greenhouse gas emissions. They also utilise about 60% of the world’s electricity. In the last decade, stringent building regulations have led to significant improvements in the quality of the thermal characteristics of many building envelopes. However, similar considerations have not been paid to the number and activities of occupants in a building, which play an increasingly important role in energy consumption, optimisation processes, and indoor air quality. More than 50% of the energy consumption could be saved in Demand Controlled Ventilation (DCV) if accurate information about the number of occupants is readily available (Mysen et al., 2005). But due to privacy concerns, designing a precise occupancy sensing/counting system is a highly challenging task. While several studies count the number of occupants in rooms/zones for the optimisation of energy consumption, insufficient information is available on the comparison, analysis and pros and cons of these occupancy estimation techniques. This paper provides a review of occupancy measurement techniques and also discusses research trends and challenges. Additionally, a novel privacy preserved occupancy monitoring solution is also proposed in this paper. Security analyses of the proposed scheme reveal that the new occupancy monitoring system is privacy preserved compared to other traditional schemes.