The use of Internet of Things (IoT) technology is crucial for improving energy efficiency in smart buildings, which could minimize global energy consumption and greenhouse gas emissions. IoT applications use numerous sensors to integrate diverse building systems, facilitating intelligent operations, real-time monitoring, and data-informed decision-making. This critical analysis of the features and adoption frameworks of IoT in smart buildings carefully investigates various applications that enhance energy management, operational efficiency, and occupant comfort. Research indicates that IoT technology may decrease energy consumption by as much as 30% and operating expenses by 20%. This paper provides a comprehensive review of significant obstacles to the use of IoT in smart buildings, including substantial initial expenditures (averaging 15% of project budgets), data security issues, and the complexity of system integration. Recommendations are offered to tackle these difficulties, emphasizing the need for established processes and improved coordination across stakeholders. The insights provided seek to influence future research initiatives and direct the academic community in construction engineering and management about the appropriate use of IoT technology in smart buildings. This study is a significant resource for academics and practitioners aiming to enhance the development and implementation of IoT solutions in the construction sector.

Climate change is a global issue that requires collective action to address. One of the most pressing concerns is reducing emissions resulting from combustion processes. The use of renewable energy sources and green energy has become a trend worldwide. Solar energy is one of the most promising sources due to its abundance and simplicity of implementation. The city of Aswan, located in the South of Egypt, has a high solar radiation that makes it ideal for utilizing solar power. The current study investigates the optimal design for a sustainable building electricity system at the Aswan Campus of the Arab Academy for Science, Technology & Maritime Transport (AASTMT) in Egypt. The campus has four electricity sources: a utility grid, PV panels, batteries, and a diesel generator, along with a weather station. Experimental investigations have been carried out in this research paper to study the performance characteristics of solar power. Moreover, HOMER pro software is used to model various configurations of the campus grid, including different photovoltaic (PV) panel types and tracking systems. The simulations are compared with real-world data collected from a weather station on campus. Additionally, CO₂ and NO₂ emissions are measured to assess the environmental impact of different scenarios. The total net cost over the life cycle is also calculated for different cases. The results demonstrate that the addition of a PV renewable system can reduce traditional grid usage by 38% and emissions by 50%. A decrease in the Levelized Cost of Energy (LOCE) from USD 0.0647 to USD 0.0535 is reported. Moreover, the difference in NCP cost between dual-axis tracking and fixed zero angle is USD 143,488. The dual degree tracker for PV panels can further enhance energy production by 30% more, compared with fixed panels, while reducing carbon dioxide emissions by more than 20%. The simulation results reveal that tracking systems provide greater energy generation, and that a cost–benefit analysis may prioritize fixed panels in some cases. The results from the HOMER software simulations closely match those of the experimental data, which is that the total presentation error does not exceed 8%, demonstrating the software’s effectiveness for optimizing renewable energy systems. This study demonstrates that a comprehensive analysis and optimization of a building’s energy sources can significantly reduce costs, lower emissions, and promote the use of renewable energy, particularly solar power.

The integration of renewable energy sources into the power grid is essential for sustainable development, yet it presents significant dependability challenges, particularly in terms of reliability, stability, and robustness due to the inherent variability of these sources. This research introduces a novel hybrid methodology that combines Monte Carlo simulation with Newton-Raphson power flow analysis to enhance the reliability assessment of grid-connected hybrid renewable energy systems. This innovative approach uniquely addresses the limitations of existing methodologies by merging the probabilistic handling of uncertainties with precise deterministic power flow analysis. Our hybrid method significantly reduces the Loss of Load Expectation (LOLE) to 5 h per year and the Loss of Load Energy Expectation (LOEE) to 200 MWh per year, outperforming traditional methods which typically report LOLEs of 2020 h/year and LOEEs of 10001000 MWh/year. Additionally, the hybrid method achieves a reduction in power losses to 1.2%, showcasing its superior efficiency compared to the 2.5% losses seen with standalone Monte Carlo methods. Real-time validation using the IEEE-30 bus model further confirms the practical applicability and robustness of our approach, making it a pivotal tool for enhancing grid stability and optimizing renewable energy integration. This research not only advances the methodology for reliability assessment but also sets a new standard for balancing accuracy and computational efficiency in energy system management. The implications of this work are far-reaching, offering significant contributions to both grid reliability and the sustainable management of renewable energy resources.

The agricultural sector emphasizes sustainable development and energy efficiency, particularly in optimizing water pumping systems for irrigation. Brushless DC (BLDC) motors are the preferred prime mover over induction motors due to their high efficiency in such applications. This article details the rotor design and analysis of an energy-efficient BLDC motor with specifications of 1 hp, 3000 rpm, and 48 V, specifically tailored for a centrifugal monoset pump for irrigation. The focus lies in achieving optimal energy efficiency through grey wolf optimization (GWO) algorithm in the rotor design to determine optimal dimensions of the Neodymium Iron Boron (NdFeB) magnet as well as its grade. The finite element method analysis software, MagNet, is used to model and analyze the BLDC motor. The motor parameters, such as speed, torque, flux functions, temperature, and efficiency, are analyzed. For performance comparison, the same model with different magnet models is also analyzed. Validation via 3D finite element analysis highlights improvements in magnet flux linkage, stator tooth flux density, and rotor inertia with increased magnet thickness. Simulation results affirm the consistent performance of the designed BLDC motor, preferably when efficiency is increased. This efficiency and the constant speed lead to an improvement in the overall conversion efficiency of 7% within its operating range, affirming that the motor pump system is energy-efficient.

Most important construction problems facing building operations are how to choose a contractor specialized in implementing major projects. In addition to that the increasing costs of raw materials, work force leading to the rise of construction costs. Therefore in this paper hierarchy method has been studied and it has been identified for organizations allowing them to minimize common risks of the decision-making process and management. Construction contractor can be prequalification using Analytical Hierarchy Process (AHP) as powerful management technique. Prequalification contractor aims at eliminating in competent contractors in the bidding process. This kind of prequalification helps both of the public and private project owners to successful achieve for required project tasks. The project will be completed with is estimated cost and time because of the contractor's skill, capability and efficiency. Case study gathers a number of contractor's or companies data. After studying Analytical Hierarchy Process (AHP) of a set of criteria, table of contractor's technical evaluation was concluded all experience, financial situation and the contractor's classification in the Union of Contractors. In addition labor's progress, availability equipment for contractor is applied using Value Engineering (VE) to raise the performance level and reducing costs. Hence, value engineering will be demonstrated, where its goal is to raise the performance level and functionality with the ability to reduce costs. The case study of this paper is a construction project of a hospital, administration building, and staff housing building. It was applied the Analytical Hierarchy Process (AHP) and was extracted contractor's evaluation table of a set of criteria (the previous experience, financial situation and the contractor's classification in the Union of Contractors. Also labor's progress, available equipment for the contractor and the contractor applying Value Engineering). The previous data are gathered through the contractor's proposal, while (VE) is applied as process steps on a construction project case study.

Unbalanced construction bidding covers different allocations of mark-up between contract project items to attempt and increase win chances with unbalance but without changing of total bid price. Many models have been developed to increase both the systemized execution and detection of unbalancing but, although unbalancing is thought to be widespread in general, substantially not known it use. Proposed unbalanced construction bidding models of many researchers neglected part of improve profitability. This paper inspects and integrates the construction bidding models techniques for determining price of each unit quantity and take advantage of bidder benefits, then all proposed mathematical models is studied carefully and more modifications will be done to tries to be fair and equitable for providing owner quantities that impact directly on items prices. Finally it was concluded that the maximum/minimum models are preferred for many world cases. At end of paper, a case of study will be presented to demonstrate the use of proposed models for optimizing project bidding. Also, this paper will serve as a guide for construction project stakeholders with effective management to perform a competitive level of project pricing.