Manu Akula

Integration of infrastructure based positioning systems and inertial navigation for ubiquitous context-aware engineering applications

This paper presents research that investigated and implemented a hybrid integrated location tracking framework that was developed by integrating infrastructure based positioning systems and inertial navigation. The authors implemented this research by using the Personal Dead Reckoning positioning system to serve as the inertial navigation based positioning system. The primary contribution of the presented work is the development and implementation of the Integrated Tracking System algorithm which was implemented in two levels. At the first level, the Integrated Tracking System (ITS) was developed by integrating Global Positioning System (GPS) and Personal Dead Reckoning (PDR) system to ubiquitously track a mobile user, in dynamic environments where GPS coverage may be uncertain. At the second level, the PDR system was integrated with a database of pre-determined known indoor location points in order to correct the accumulated drift error during a mobile users navigation in an indoor environment. Finally, a hybrid tracking system was developed and implemented by integrating the PDR system with the mobile users intervention and discernment of the environment. The implementation and the results obtained from validation experiments performed on the aforementioned hybrid tracking systems demonstrate the potential of using hybrid tracking for determining the spatial context of mobile users in ubiquitous context-aware engineering applications.

Leveraging BIM for Automated Fault Detection in Operational Buildings

Building Information Modeling (BIM) is an increasingly popular method for generating and managing facility information during the life cycle of a building, ranging from facility conceptualization, through design, construction and its operational life. Organizations involved in Facility Management (FM) have the opportunity to use BIM as a knowledge repository to document evolving facility information and to support decisions made by the facility managers during the operational life of a facility. This paper demonstrates the potential of using BIM to develop algorithms that automate decision making for FM applications. The potential of utilizing BIM as an analysis tool is demonstrated through the scenario of HVAC (Heating, Ventilation, and Air Conditioning) system failure in an operating facility. In case of a typical HVAC malfunction today, facility occupants record complaints in a ticketing database maintained by the FM organization. Upon receiving notification of HVAC system failure, facility inspectors visit the location to confirm the reported failure. Upon confirmation, facility managers review building plans and specifications to develop a detailed plan of action to repair any HVAC components suspected of damage. Based on the plan of action, inspectors visit the facility to inspect and, in case of damage, repair the appropriate HVAC system components. These FM practices – as currently implemented across the industry – are labor intensive, time consuming, and often rely on unreliable and outdated information. To address these shortcomings, the authors propose an alternative methodology of HVAC fault detection in operational buildings. The authors implement an algorithm that leverages complaint ticket data and automates BIM to determine potentially damaged HVAC system components. Based on the list of HVAC components suspected of damage, the algorithm develops a plan of action for the facility inspectors. Finally, the authors discuss the advantages of the proposed method as well as the challenges of implementing automated BIM-enabled decision making processes in the FM industry.

Automated building information modeling for fault detection and diagnostics in commercial HVAC systems

Purpose Organizations involved in facility management (FM) can use building information modeling (BIM) as a knowledge repository to document evolving facility information and to support decisions made by the facility managers during the operational life of a facility. Despite ongoing advances in FM technologies, FM practices in most facilities are still labor intensive, time consuming and often rely on unreliable and outdated information. To address these shortcomings, the purpose of this study is to propose an automated approach that demonstrates the potential of using BIM to develop algorithms that automate decision-making for FM applications. Design/methodology/approach A BIM plug-in tool is developed that uses a fault detection and diagnostics (FDD) algorithm to automate the process of detecting malfunctioning heating, ventilation, and air conditioning (HVAC) equipment. The algorithm connects to a complaint ticket database and automates BIM to determine potentially damaged HVAC system components and develops a plan of action for the facility inspectors accordingly. The approach has been implemented as a case study in an operating facility to improve the process of HVAC system diagnosis and repair. Findings By implementing the proposed application in a case study, the authors found that automated BIM approaches such as the one developed in this study, can be highly beneficial in FM practices by increasing productivity and lowering costs associated with decision-making. Originality/value This study introduces an innovative approach that leverages BIM for automated fault detection in operational buildings. FM personnel in charge of HVAC inspection and repair can highly benefit from the proposed approach, as it eliminates the time required to locate HVAC equipment at fault manually.

Augmenting BIM with 3D Imaging Data to Control Drilling for Embeds into Reinforced Concrete Bridge Decks

Placing embeds into reinforced concrete structures, after concrete is poured, without damaging reinforcement bars (rebar) is an industry-wide challenge encountered across the construction industry. In concrete structures such as containment vessels, bridge decks and post-tensioned concrete floors damaging rebar may compromise structural integrity and result in considerable rework. Although negative impressions for embeds can be made by placing various objects such as wooden dowels or steel rods into the rebar cage prior to pouring the concrete (and removing them once the concrete has partially or fully set), this practice is labor intensive and time consuming. A method of mapping the locations of the rebar free spaces before pouring and controlling the drilling process in real-time could have significant benefits. This paper presents research that investigated and implemented conceptual solutions for processing and incorporating point cloud data obtained from various 3D-imaging technologies into the drilling process. The 3D imaging technologies were used to map the locations of rebar within a replica of a section of a railway bridge deck. Once the point clouds were processed, zones that are safe for drilling are automatically detected and saved as a Building Information Model (BIM) that is then used to provide real-time feedback to the drill operator about whether it is safe to continue drilling based on the position and orientation of the drill. A conceptual method for providing visual feedback about the rebar-free zones to the drill operator using a laser projector was also developed. Finally, a visualization method for comparing the data obtained from the various 3D imaging technologies using the BIM is discussed.

Context-Aware Framework for Highway Bridge Inspections

AbstractBridge inspections are tedious, time consuming, and complex tasks in the field that require highly specific information pertinent to the decisions at hand. The use of a centralized inspection database and bridge inspection reporting software has been explored by several state DOTs in recent years. During an inspection routine, the inspector visually assesses the condition of a particular bridge component. Based on a priori knowledge of the bridge components’ taxonomic hierarchy and ontology, the inspector navigates to the form corresponding to the component. The inspector then reports the component’s condition to the database. Context-aware computing offers the possibility to make inspections more efficient by reducing the time required to navigate the software and the effort spent by inspectors to learn, remember, and recall the taxonomic hierarchy and ontology of bridge components. Context-aware computing leverages environmental variables, which define the inspector’s context, and delivers strea...

Electromechanical Development of a Low Cost End Effector Pose Estimation System for Articulated Excavators

Vision-based pose estimation, in which optical cameras monitor fiducial markers to determine the three dimensional positioning and orientation of an articulated machine’s end effector, offers a promising low-cost alternative to currently available sensor packages that are non-ubiquitous and cost prohibitive for a large portion of the market. Whereas traditional sensor systems determine end effector pose via kinematic chains passing through the links of a machine, optical sensor systems are capable of determining pose by observing an end effector directly. However, since markers cannot be mounted on an excavator’s bucket for occlusion and durability reasons, a short kinematic chain must be used. An electromechanical design is proposed to provide such function for a low cost marker-based excavator pose estimation system. Several iterations of design and experimentation are discussed, including a four-bar linkage system, a synchronous belt system, a bucket linkage system, and a cable potentiometer system. The four-bar linkage and toothed belt systems were designed to transmit bucket angle information to cameras through the manipulation of a marker’s pose, but were found to possess Gimbal lock and practicality issues, respectively. To overcome such issues, a generalized mapping approach was adopted and implemented in a bucket linkage design and a cable potentiometer design. The viability of the cable potentiometer system was experimentally confirmed, along with the identification of further work needed to refine the technology for large-scale practical implementation.

Context-Aware Computing Framework for Improved Bridge Inspection

Bridge inspections are tedious, time consuming and complex tasks in the field which require highly specific information pertinent to the decisions at hand. Bridge inspectors assess the condition of bridge components based on standard rating guidelines and previous bridge inspection reports. Most bridge inspections are currently conducted manually with little support from Information Technology and the captured data must be manually entered into a computer system for later retrieval. Context-aware computing promises to make inspections more efficient by automatically associating captured data with bridge design data in a database. This paper presents a context-aware computing platform that facilitates bi-directional flow of information and supplements field inspectors with relevant data to support their operations. The implemented context-aware computing framework automatically interprets the spatial-context of the bridge inspector based on the inspector’s position and head orientation. The framework also provides methods to map and store the geometric representation of the bridge-inspection elements in a database. To validate the framework, a context-aware computing application was designed. The application coordinates the inspector’s spatial-context with the bridge model in the database so that the inspector is provided with data that is relevant to his/her context. The application also facilitates bi-directional communication between the inspector and the bridge inspection database management system. Finally, the characteristics of context-aware computing supported bridge inspection routines are compared against the traditional (manual) approach to bridge inspection routines. IMPORTANCE OF THE RESEARCH