Gulben Calis

Application Areas and Data Requirements for BIM-Enabled Facilities Management

Facilities management (FM) encompasses and requires multidisciplinary activities, and thus has extensive information requirements. While some of these needs are addressed by several existing FM information systems, building information modeling (BIM), which is becoming widely adopted by the construction industry, holds undeveloped possibilities for providing and supporting FM practices with its functionalities of visualization, analysis, control, and so on. This paper explores how BIM can be a beneficial platform for supplementing FM practices. An online survey and face-to-face interviews were conducted to assess the current status of BIM implementations in FM, potential applications, and the level of interest in the utilization of BIM. Interactions between BIM and FM are defined by illustrating application areas and data requirements for BIM-enabled FM practices. Highlighting the synergy between the two, this paper can help professionals recognize potential areas in which BIM can be useful in FM practices.

Deployment Strategies and Performance Evaluation of a Virtual-Tag-Enabled Indoor Location Sensing Approach

AbstractIndoor location information is valuable to the construction industry for a wide range of purposes, including on-site personnel safety, asset security, facility maintenance, and in-building emergency response. Indoor location sensing includes presence detection and location calculation, for which a number of technologies and algorithms have been tested. To advance the research in this area, the paper proposes an improved radio frequency identification (RFID)-based location-sensing algorithm that uses virtual tags to increase cost effectiveness and robustness. A series of tests were conducted in a controlled environment, and the findings on algorithm parameter optimization, equipment deployment strategies, system accuracy/cost tradeoff, and robustness are presented in the paper. The results show that a mean accuracy of 1.94±0.17  m for stationary targets and 1.42±0.49  m for mobile targets can be achieved, and that the system holds promise for robustness. Virtual tags are proven to reduce cost and i...

Assessment of WSN and RFID Technologies for Real-Time Occupancy Information

Real-time occupancy information is valuable to the building industry for a wide variety of applications such as on-site safety management, energy conservation, emergency response and so on. With the emergence of various technologies that can potentially be used for indoor location sensing (ILS), the building industry is in search for an ILS solution to provide accurate and cost efficient occupancy information. This study assesses two ILS systems that are built on two promising modalities: radio frequency identification (RFID) and wireless sensor networks (WSNs). Two algorithms were proposed and tested in a computer lab with an area of 235 m. Six occupants, who were attached with both RFID tags and WSN nodes, were tracked simultaneously. The occupants remained seated throughout the test, and the occupancy was monitored. The results show that the proposed systems were able to provide accurate room level occupancy information majority of the time, and that the choice of algorithm and technology affected the uniformity of the results.

RFID-Based Occupancy Detection Solution for Optimizing HVAC Energy Consumption

Current building climate control systems often rely on predetermined maximum occupancy numbers coupled with temperature sensor data to regulate heating, ventilation, and air conditioning (HVAC). However, rooms and zones in a building are not always fully occupied. Real-time occupancy information can potentially be used to reduce energy consumption. The paper proposes an RFID-based occupancy detection solution to address the need for real-time in-building occupancy information. The proposed solution can track real-time location of tagged occupants, and report the occupancy at the zone level. A prototype was built and tested in a campus-dining hall with three zones. Occupants who were waiting in a queue, walking, or sitting were equipped with active RFID tags. The results demonstrated that the location of occupants could be estimated and 71% of the occupants could be detected at the right predefined zone. Based on the findings, detailed and operable strategies for optimizing HVAC-related building energy consumption by using occupancy information are proposed.

Design and Evaluation of Algorithm and Deployment Parameters for an RFID- Based Indoor Location Sensing Solution

Indoor location information is valuable to the building industry for a wide range of purposes such as on-site personnel safety, asset security, facility maintenance, and in-building emergency response. Despite the availability of applicable technologies, there is no indoor location sensing solution that is cost efficient and, therefore, widely adapted by the industry while providing highly accurate location information. The authors have designed and tested an RFID-based location sensing algorithm that uses virtual reference tags, which eliminates the need for collecting prior localization data, increases the accuracy of the location information, and potentially reduces the deployment costs. The paper summarizes a series of 9 field tests, and presents findings on algorithm parameter optimization and equipment deployment strategies. The test results show that the number of nearest neighbors, k=4 and arithmetical averages yielded best results, and the performance of the proposed solution was consistent for different reference tag layouts.

Impact of Ambient Temperature, Tag/Antenna Orientation and Distance on the Performance of Radio Frequency Identification in Construction Industry

Construction industry has been utilizing the RFID technology in various applications such as increasing productivity, enhancing safety, and improving quality, mostly through the analysis of the received signal-strength index (RSSI) readings. However, RSSI readings are directly influenced by environmental factors which can decrease the effectiveness of the RFID technology. This study evaluates the effects of environmental factors on RSSI readings. Evaluated environmental factors include: (1) relative orientation between tags and antennae, (2) temperature of the environment, (3) distance between tags and antennae. A series of tests were conducted in an educational building and RSSI readings collected from the tests were evaluated by statistical analysis to quantify environmental effects on RFID performance. The results show that orientation and distance between tags and antennae had significant effects on RSSI readings. Moreover, very weak effects on RSSI readings were observed under varying indoor temperatures.

Thermal Comfort and Occupant Satisfaction of a Mosque in a Hot and Humid Climate

Mosques are distinguished from other types of buildings by having an intermittent operation schedule. They are partially or fully occupied five times a day and the maximum occupancy is expected to occur on Friday prayers. As buildings with intermittent occupancy may not perform the same thermally as typical commercial and residential facilities, thermal comfort conditions and perception of occupants have to be investigated. This paper presents the results of a study monitoring indoor environmental conditions of a mosque in order to assess thermal comfort conditions. A historic mosque, which is located in a hot and humid climatic region of Turkey, was selected as a test building and thermal comfort conditions were monitored during two Friday prayers in August and September. Indoor air temperature, relative humidity and air velocity were collected via data loggers. The predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD) indices were calculated and evaluated using the ASHRAE 55-2010 standard. In addition to this, a questionnaire based on Fanger’s seven-point scale was conducted to understand the thermal sensation and preference of occupants. A comparison is provided to highlight the difference between the calculated and perceived satisfaction of occupants.

Forecasting Occupancy for Demand Driven HVAC Operations Using Time Series Analysis

Building heating, ventilation, and air conditioning (HVAC) systems contribute substantially to the energy consumption of buildings. Today, traditional HVAC systems mostly operate according to the maximum occupancy assumption, which in turn increases energy consumption during periods of low occupancy. Although, recently, implementing demand-driven HVAC operations are accepted as an innovate approach for reducing HVAC-related energy consumption, occupancy forecast is important to realize demand-driven HVAC operations in buildings. This study aims at using time series models in order to forecast the daily number of bank customers in a financial center of a bank, which is located in Izmir, Turkey. Data were collected from the computerized tracking system for a period of 60 weeks and two forecasting methods were used: 1) Decomposition Method, 2) Box-Jenkins Method. To determine the final model identified via the Box-Jenkins Method, goodness-of-fit, residual analysis and Akaike information criterion were taken into consideration. The results show that the SARIMA model with a MAPE of 11% yields a good occupancy forecast for supporting demand-driven HVAC operations.