Developing Mobile BIM/2D Barcode-Based Automated Facility Management System

Facility management (FM) has become an important topic in research on the operation and maintenance phase. Managing the work of FM effectively is extremely difficult owing to the variety of environments. One of the difficulties is the performance of two-dimensional (2D) graphics when depicting facilities. Building information modeling (BIM) uses precise geometry and relevant data to support the facilities depicted in three-dimensional (3D) object-oriented computer-aided design (CAD). This paper proposes a new and practical methodology with application to FM that uses an integrated 2D barcode and the BIM approach. Using 2D barcode and BIM technologies, this study proposes a mobile automated BIM-based facility management (BIMFM) system for FM staff in the operation and maintenance phase. The mobile automated BIMFM system is then applied in a selected case study of a commercial building project in Taiwan to verify the proposed methodology and demonstrate its effectiveness in FM practice. The combined results demonstrate that a BIMFM-like system can be an effective mobile automated FM tool. The advantage of the mobile automated BIMFM system lies not only in improving FM work efficiency for the FM staff but also in facilitating FM updates and transfers in the BIM environment

Vision Based Extraction of Nutrition Information from Skewed Nutrition Labels

An important component of a healthy diet is the comprehension and retention of nutritional information and understanding of how different food items and nutritional constituents affect our bodies. In the U.S. and many other countries, nutritional information is primarily conveyed to consumers through nutrition labels (NLs) which can be found in all packaged food products. However, sometimes it becomes really challenging to utilize all this information available in these NLs even for consumers who are health conscious as they might not be familiar with nutritional terms or find it difficult to integrate nutritional data collection into their daily activities due to lack of time, motivation, or training. So it is essential to automate this data collection and interpretation process by integrating Computer Vision based algorithms to extract nutritional information from NLs because it improves the user’s ability to engage in continuous nutritional data collection and analysis. To make nutritional data collection more manageable and enjoyable for the users, we present a Proactive NUTrition Management System (PNUTS). PNUTS seeks to shift current research and clinical practices in nutrition management toward persuasion, automated nutritional information processing, and context-sensitive nutrition decision support. PNUTS consists of two modules, firstly a barcode scanning module which runs on smart phones and is capable of vision-based localization of One Dimensional (1D) Universal Product Code (UPC) and International Article Number (EAN) barcodes with relaxed pitch, roll, and yaw camera alignment constraints. The algorithm localizes barcodes in images by computing Dominant Orientations of Gradients (DOGs) of image segments and grouping smaller segments with similar DOGs into larger connected components. Connected components that pass given morphological criteria are marked as potential barcodes. The algorithm is implemented in a distributed, cloud-based system. The system’s front end is a smartphone application that runs on Android smartphones with Android 4.2 or higher. The system’s back end is deployed on a five node Linux cluster where images are processed. The algorithm was evaluated on a corpus of 7,545 images extracted from 506 videos of bags, bottles, boxes, and cans in a supermarket. The DOG algorithm was coupled to our in-place scanner for 1D UPC and EAN barcodes. The scanner receives from the DOG algorithm the rectangular planar dimensions of a connected component and the component’s dominant gradient orientation angle referred to as the skew angle. The scanner draws several scan lines at that skew angle within the component to recognize the barcode in place without any rotations. The scanner coupled to the localizer was tested on the same corpus of 7,545 images. Laboratory experiments indicate that the system can localize and scan barcodes of any orientation in the yaw plane, of up to 73.28 degrees in the pitch plane, and of up to 55.5 degrees in the roll plane. The videos have been made public for all interested research communities to replicate our findings or to use them in their own research. The front end Android application is available for free download at Google Play under the title of NutriGlass. This module is also coupled to a comprehensive NL database from which nutritional information can be retrieved on demand. Currently our NL database consists of more than 230,000 products. The second module of PNUTS is an algorithm whose objective is to determine the text skew angle of an NL image without constraining the angle’s magnitude. The horizontal, vertical, and diagonal matrices of the (Two Dimensional) 2D Haar Wavelet Transform are used to identify 2D points with significant intensity changes. The set of points is bounded with a minimum area rectangle whose rotation angle is the text’s skew. The algorithm’s performance is compared with the performance of five text skew detection algorithms on 1001 U.S. nutrition label images and 2200 single- and multi-column document images in multiple languages. To ensure the reproducibility of the reported results, the source code of the algorithm and the image data have been made publicly available. If the skew angle is estimated correctly, optical character recognition (OCR) techniques can be used to extract nutrition information

Rationally designed substrates for SERS biosensing

Thesis (Ph.D.)--Boston UniversityThe large electromagnetic field enhancement provided by nanostructured noble metal surfaces forms the foundation for a series of enabling optical analytical techniques, such as surface enhanced Raman spectroscopy (SERS), surface enhanced IR absorption spectroscopy (SEIRA), surface enhanced fluorescent microscopy (SEF), to name only a few. Critical sensing applications have, however, other substrate requirements than mere peak signal enhancement. The substrate needs to be reliable, provide reproducible signal enhancements, and be amenable to a combination with microfluidic chips or other integrated sensor platforms. These needs motivate the development of engineerable SERS substrate "chips" with defined near- and far-field responses. In this dissertation, two types of rationally designed SERS substrates - nanoparticle cluster arrays (NCAs) and SERS stamp - will be introduced and characterized. NCAs were fabricated through a newly developed template guided self-assembly fabrication approach, in which chemically synthesized nanoparticles are integrated into predefined patterns using a hybrid top-down/bottom-up approach. Since this method relies on chemically defined building blocks, it can overcome the resolution limit of conventional lithographical methods and facilitates higher structural complexity. NCAs sustain near-field interactions within individual clusters as well as between entire neighboring clusters and create a multi-scale cascaded E-field enhancement throughout the entire array. SERS stamps were generated using an oblique angle metal deposition on a lithographically defined piston. When mounted on a nanopositioning stage, the SERS stamps were enabled to contact biological surfaces with pristine nanostructured metal surfaces for a label-free spectroscopic characterization. The developed engineered substrates were applied and tested in critical sensing applications, including the ultratrace detection of explosive vapors, the rapid discrimination of bacterial pathogens, and the label-free monitoring of the enzymatic degradation of pericellular matrices of cancer cells

Location-based and contextual mobile learning. A STELLAR Small-Scale Study

This study starts from several inputs that the partners have collected from previous and current running research projects and a workshop organised at the STELLAR Alpine Rendevous 2010. In the study, several steps have been taken, firstly a literature review and analysis of existing systems; secondly, mobile learning experts have been involved in a concept mapping study to identify the main challenges that can be solved via mobile learning; and thirdly, an identification of educational patterns based on these examples has been done. Out of this study the partners aim to develop an educational framework for contextual learning as a unifying approach in the field. Therefore one of our central research questions is: how can we investigate, theorise, model and support contextual learning

Overview of building information modelling in healthcare projects

In this paper, we explore how BIM functionalities together with novel management concepts and methods have been utilized in thirteen hospital projects in the United States and the United Kingdom. Secondary data collection and analysis were used as the method. Initial findings indicate that the utilization of BIM enables a holistic view of project delivery and helps to integrate project parties into a collaborative process. The initiative to implement BIM must come from the top down to enable early involvement of all key stakeholders. It seems that it is rather resistance from people to adapt to the new way of working and thinking than immaturity of technology that hinders the utilization of BIM

Design and application of a contact barcode reader, for use on low-visibility printed conductive patterns

This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University.This thesis presents the design and development of a hand-held electronic reader, designed to decode conductive patterns printed on a paper substrate. Data read from the patterns, by the reader, is used to trigger events in the digital domain. The reader and associated conductive patterns are devices for linking paper documents with the digital world. The patterns are formed by masking conductive-coated paper with a non-conductive, printed lacquer. The reader is a low cost and ergonomic device, capable of transmitting the embedded data from the conductive paper to the computer. The first reader designed and developed was tethered to a computer by data cable, using the USB communication protocol. The second design was developed further, with transmission of data achieved by replacing the cable with short-range Bluetooth wireless technology. Both devices were designed and developed using embedded systems and low cost electronic components. Additional work was undertaken to optimise the device's mechanical structure, ergonomics and integration of hardware. Alongside the development of the reader, test and development work was carried out to optimise the printed media, in materials and design. User trials demonstrated that the complete printed and reading system was functional, with varied rates of success among participants. Further work is required to improve the conductivity of the coated paper, and the accuracy of the decoding algorithm.This work resulted from a research project funded by EU FP6

2D-barcode for mobile devices

2D-barcodes were designed to carry significantly more data than its 1D counterpart. These codes are often used in industrial information tagging applications where high data capacity, mobility, and data robustness are required. Wireless mobile devices such as camera phones and Portable Digital Assistants (PDAs) have evolved from just a mobile voice communication device to what is now a mobile multimedia computing platform. Recent integration of these two mobile technologies has sparked some interesting applications where 2D-barcodes work as visual tags and/or information source and camera phones performs image processing tasks on the device itself. One of such applications is hyperlink establishment. The 2D symbol captured by a camera phone is decoded by the software installed in the phone. Then the web site indicated by the data encoded in a symbol is automatically accessed and shown in the display of the camera phone. Nonetheless, this new mobile applications area is still at its infancy. Each proposed mobile 2D-barcode application has its own choice of code, but no standard exists nor is there any study done on what are the criteria for setting a standard 2D-barcode for mobile phones. This study intends to address this void. The first phase of the study is qualitative examination. In order to select a best standard 2D-barcode, firstly, features desirable for a standard 2D-barcode that is optimized for the mobile phone platform are identified. The second step is to establish the criteria based on the features identified. These features are based on the operating limitations and attributes of camera phones in general use today. All published and accessible 2D-barcodes are thoroughly examined in terms of criteria set for the selection of a best 2D-barcode for camera phone applications. In the second phase, the 2D-barcodes that have higher potential to be chosen as a standard code are experimentally examined against the three criteria: light condition, distance, whether or not a 2D-barcode supports VGA resolution. Each sample 2D-barcode is captured by a camera phone with VGA resolution and the outcome is tested using an image analysis tool written in the scientific language called MATLAB. The outcome of this study is the selection of the most suitable 2D-barcode for applications where mobile devices such as camera phones are utilized