BIMp-Chart—A Global Decision Support System for Measuring BIM Implementation Level in Construction Organizations

Potential features of building information modeling (BIM) for application of project management knowledge areas in the construction industry

The construction industry (CI) plays a vital role in infrastructure development and improves the socio-economic status with employment opportunities and contribution to gross domestic progress (GDP) of countries. However, its productivity has diminished in recent years due to increasing complexities in construction projects (CPs) and lack of adoption of novel technologies such as Building Information Modeling (BIM). Also, there is a significant need of polishing the capabilities of construction practitioners to meet the project requirements in agreement with project management knowledge areas (PMKAs). This study, therefore, focused on identification and evaluation of factors necessary for measurement of extent of application of PMKAs. Subsequently, noteworthy features of BIM helpful for enhancing the capabilities of project managers (PMs) in application of PMKAs were identified from literature. A total of thirty-three factors for measurement of extent of application of PMKAs and sixty-six features of BIM helpful in enhancing the capabilities of PMs in application of PMKAs were found. The detailed study and analysis of these ninety-nine factors with the help of previous studies suggested that extent of application of PMKAs is measured with three sub-tasks i.e., plan, manage/develop, and monitor/control. In addition, by virtue of remarkable features and services of BIM, it helps in enhancing the capabilities of PMs in applying PMKAs: project integration, scope, cost, time, quality, resource, communications, procurement, risk, safety, and stakeholder management.

Modeling the Critical Success Factors for BIM Implementation in Developing Countries: Sampling the Turkish AEC Industry

One of the latest advancements transforming the global architectural, engineering, and construction (AEC) industry is building information modeling (BIM). Although BIM implementation is at high level in developed countries, it is at a lower level in developing countries. BIM is new to the construction industry in Turkey, with only minor construction firms having implemented it. When making projections based on the current state of the Turkish AEC industry, it is foreseen that it will become mandatory in the near future. Considering this projection, it is doubtful that many construction companies will be caught unprepared for this situation and will not know how to implement BIM. Therefore, this study aimed to identify and model the critical success factors for BIM implementation and their impact size in order to gain insight for the fast and efficient implementation of BIM among construction firms in the Turkish AEC industry, which can be generalized for most developing countries. To reach these aims, a questionnaire was designed with 41 identified success criteria (SC) that were derived through a systematic literature review (SLR). The survey was conducted on construction professionals who actively implement BIM technology at their occupied firms in Turkey and they were asked to rank the importance of 41 SC on a five-point Likert scale. The sampling frame consisted of architects and civil engineers, and in total, 243 responses were received. The differentiation between SC and critical success criteria (CSC) was obtained by using a normalized mean cutoff value. An exploratory factor analysis (EFA) was used to identify the critical success factors (CSFs), and structural equation modeling (SEM) was used to examine the underlying size effects of each CSF on BIM implementation in the Turkish AEC industry. The results of this study reveal 20 CSC for successful BIM implementation, and EFA exhibited three CSFs from 20 CSC. Three critical success factors for BIM implementation in the Turkish construction industry were determined and grouped into two categories. “Awareness of technological benefits” and “organizational readiness and competitive advantages” formed one group and are the most influential critical success factors for BIM implementation. “Motivation of management regarding BIM” formed the second group of critical success factors that have a significant effect.

Using Adaptive Sensors for Optimised Target Coverage in Wireless Sensor Networks

Innovation in wireless communications and microtechnology has progressed day by day, and this has resulted in the creation of wireless sensor networks. This technology is utilised in a variety of settings, including battlefield surveillance, home security, and healthcare monitoring, among others. However, since tiny batteries with very little power are used, this technology has power and target monitoring issues. With the development of various architectures and algorithms, considerable research has been done to address these problems. The adaptive learning automata algorithm (ALAA) is a scheduling machine learning method that is utilised in this study. It offers a time-saving scheduling method. As a result, each sensor node in the network has been outfitted with learning automata, allowing them to choose their appropriate state at any given moment. The sensor is in one of two states: active or sleep. Several experiments were conducted to get the findings of the suggested method. Different parameters are utilised in this experiment to verify the consistency of the method for scheduling the sensor node so that it can cover all of the targets while using less power. The experimental findings indicate that the proposed method is an effective approach to schedule sensor nodes to monitor all targets while using less electricity. Finally, we have benchmarked our technique against the LADSC scheduling algorithm. All of the experimental data collected thus far demonstrate that the suggested method has justified the problem description and achieved the project’s aim. Thus, while constructing an actual sensor network, our suggested algorithm may be utilised as a useful technique for scheduling sensor nodes.

Assessing Rainwater Harvesting Potential in Urban Areas: A Building Information Modelling (BIM) Approach

Water scarcity has become a major problem for many countries, resulting in declining water supply and creating a need to find alternative solutions. One potential solution is rainwater harvesting (RwH), which allows rainwater to be stored for human needs. This study develops an RwH assessment system through building information modeling (BIM). For this purpose, a hydrological study of Cfa-type climate cities is conducted with the example of Islamabad, Pakistan. The monthly rainfall data of three sites were assessed to determine the volume of the accumulated rainwater and its potential to meet human needs. The average number of people living in a house is taken as the household number. Household number or of the number of employees working at a small enterprise, roofing material, and rooftop area are used as the key parameters for pertinent assessment in the BIM. The data simulated by BIM highlight the RwH potential using five people per house as the occupancy and a 90 m2 rooftop area for residential buildings or small enterprises as parameters. The results show that the selected sites can collect as much as 8,190 L/yr of rainwater (48 L/person/day) to 103,300 L/yr of rainwater (56 L/person/day). This much water is enough to fulfill the daily demands of up to five people. Therefore, it is established that the study area has an RwH potential that is able to meet the expected demands. This study presents a baseline approach for RwH to address water scarcity issues for residential buildings and factories of the future.

Facilitators and Barriers in Applying Building Information Modeling (BIM) for Construction Industry

The authors provide a holistic perspective to enhance BIM working environment for more efficient smart construction settlements. An in-depth survey with 40 questionnaires was distributed to 100 professionals in construction, design, engineering, government. Although 45% of the respondents have received a certain form of BIM education, more than 94% of the respondents have answered that there should be a formal BIM education. Both design and construction experts have reported that the biggest advantage of using BIM is in its error checking ability. It can reduce design errors and increase construction ability. More than 79% of the respondents agreed upon a proper compensation for BIM implementation. The majority of opinions have revealed that there should be an increase in construction and design fees. There are a number issues for a successful BIM application: (1) guidelines and details for BIM work and delivery; (2) more standardized BIM education; and (3) a proper compensation system for BIM work. The results show that BIM professionals are ready to adopt the consequences of using BIM, but administrative and institutional preparations are not available beforehand. There should be a higher level of regulatory concern and provision of administrative solutions for successful BIM applications.