A systematic approach for monitoring and evaluating the construction project progress

A persistent problem in construction is to document changes which occur in the field and to prepare the as-built schedule. In current practice, deviations from planned performance can only be reported after significant time has elapsed and manual monitoring of the construction activities are costly and error prone. Availability of advanced portable computing, multimedia and wireless communication allows, even encourages fundamental changes in many jobsite processes. However a recent investigation indicated that there is a lack of systematic and automated evaluation and monitoring in construction projects. The aim of this study is to identifytechniques that can be used in the construction industry for monitoring and evaluating the physical progress, and also to establish how current computer technology can be utilised for monitoring the actual physical progress at the construction site. This study discusses the results of questionnaire survey conducted within Malaysian Construction Industry and suggests a prototype system, namely Digitalising Construction Monitoring (DCM). DCM prototype system integrates the information from construction drawings, digital images of construction site progress and planned schedule of work. Using emerging technologies and information system the DCM re-engineer the traditional practice for monitoring the project progress. This system can automatically interpret CAD drawings of buildings and extract data on its structural components and store in database. It can also extract the engineering information from digital images and when these two databases are simulated the percentage of progress can be calculated and viewed in Microsoft Project automatically. The application of DCM system for monitoring the project progress enables project management teams to better track and controls the productivity and quality of construction projects. The use of the DCM can help resident engineer, construction manager and site engineer in monitoring and evaluating project performance. This model will improve decision-making process and provides better mechanism for advanced project management

Developing a MongoDB Monitoring System using NoSQL Databases for Monitored Data Management

MongoDB is a NoSQL database, specifically used to efficiently store and access a large quantity of unstructured data over a distributed cluster of nodes. As the number of nodes in the cluster increases, it becomes difficult to manually monitor different components of the database. This poses an interesting problem of monitoring the MongoDB database to view the state of the system at any point. Although a few proprietary monitoring tools exist to monitor MongoDB clusters, they are not freely available for use in academia. Therefore, the focus of this project is to create a monitoring system that is completely built from open-source resources. To automatically monitor a MongoDB cluster, several components are to be built: monitoring agents that obtain this information from the nodes in the cluster, storage mechanisms to save this information for future use and write buffers to temporarily hold monitored records before they are written to storage. The monitoring agents have to be created to obtain only the information that a user of a monitoring system might find useful. Since monitored data is expected to be of high volume and velocity, NoSQL databases are ideal candidates for the storage component of the monitoring system. MongoDB, Cassandra, and OpenTSDB are identified as suitable candidates and their performances are compared with respect to several aspects such as read and write performance and storage requirements. In an attempt to improve the write performance of the system, the performance impact of adding a BigQueue as a write buffer to the storage is also studied

YUCSA: A CLIPS expert database system to monitor academic performance

The York University CLIPS Student Administrator (YUCSA), an expert database system implemented in C Language Integrated Processing System (CLIPS), for monitoring the academic performance of undergraduate students at York University, is discussed. The expert system component in the system has already been implemented for two major departments, and it is under testing and enhancement for more departments. Also, more elaborate user interfaces are under development. We describe the design and implementation of the system, problems encountered, and immediate future plans. The system has excellent maintainability and it is very efficient, taking less than one minute to complete an assessment of one student

Networked Geotechnical Near Real-Time Monitoring for Large Urban Excavation Using Multiple Wireless Sensors

A massive urban excavation is required to construct the below-grade rail platforms for the Transbay Transit Center. A performance-based approach was used to design the minimum stiffness of the shoring system to limit excavation-induced ground movements to appropriate magnitudes and minimize impact to adjacent infrastructure. During construction, a fully-automated near real-time digital geotechnical monitoring system that integrates wireless sensor data streams into an integrated database and decision support system called the Global Analyzer is used to track the performance of this excavation. Instrumentation used for monitoring includes inclinometers, deep settlement markers, extensometers, piezometers, and an automated total station network. Some of the advantages of the Global Analyzer system include (a) integration of all project monitoring data and construction history information in a centralized database, (b) the ability to compare measured and estimated or target performance, (c) the use of early indicators to understand problems areas prior to excavation reaching critical stages, (d) the distribution of geotechnical monitoring data to adjacent building owners and other stakeholders through a web-based portal, and (e) the generation of computer generated email alerts when threshold values are exceeded by a given instrument. The Global Analyzer is a key tool in supporting an efficient decision process informed by more complete and timely performance data. It represents a component of the decision support process needed in the observational approach and deformation control. This application is relatively new to such a large scale project in the US and provides an example of a large complex data collection and distribution system. The monitoring process used for this project takes advantage of the latest communications technologies in the monitoring of the construction of the Transbay Transit Center excavation in its complex urban environment

Practical Database Design for Industrial Maintenance System

This paper describes how a database design can play an important role for developing practical industrial maintenance system. The good database design will in return give a better information sharing and good system in term of data accessibility. The design of the database are presented and illustrated by a case. The preliminary result presented to show that is possible to access a more correct view of the situation in the system development and thereby obtain a better base for making maintenance decisions. The database supports the development of applications e.g. for monitoring the performance of a maintenance in the production, for deciding the most appropriate maintenance policy or for simulating possible maintenance solutions

First experiences with the ATLAS Pixel Detector Control System at the Combined Test Beam 2004

Detector control systems (DCS) include the read out, control and supervision of hardware devices as well as the monitoring of external systems like cooling system and the processing of control data. The implementation of such a system in the final experiment has also to provide the communication with the trigger and data acquisition system (TDAQ). In addition, conditions data which describe the status of the pixel detector modules and their environment must be logged and stored in a common LHC wide database system. At the combined test beam all ATLAS subdetectors were operated together for the first time over a longer period. To ensure the functionality of the pixel detector a control system was set up. We describe the architecture chosen for the pixel detector control system, the interfaces to hardware devices, the interfaces to the users and the performance of our system. The embedding of the DCS in the common infrastructure of the combined test beam and also its communication with surrounding systems will be discussed in some detail.Comment: 6 pages, 9 figures, Pixel 2005 proceedings preprin