A Review on Energy Consumption Optimization Techniques in IoT Based Smart Building Environments

In recent years, due to the unnecessary wastage of electrical energy in residential buildings, the requirement of energy optimization and user comfort has gained vital importance. In the literature, various techniques have been proposed addressing the energy optimization problem. The goal of each technique was to maintain a balance between user comfort and energy requirements such that the user can achieve the desired comfort level with the minimum amount of energy consumption. Researchers have addressed the issue with the help of different optimization algorithms and variations in the parameters to reduce energy consumption. To the best of our knowledge, this problem is not solved yet due to its challenging nature. The gap in the literature is due to the advancements in the technology and drawbacks of the optimization algorithms and the introduction of different new optimization algorithms. Further, many newly proposed optimization algorithms which have produced better accuracy on the benchmark instances but have not been applied yet for the optimization of energy consumption in smart homes. In this paper, we have carried out a detailed literature review of the techniques used for the optimization of energy consumption and scheduling in smart homes. The detailed discussion has been carried out on different factors contributing towards thermal comfort, visual comfort, and air quality comfort. We have also reviewed the fog and edge computing techniques used in smart homes

The effects of school reform under NCLB waivers: Evidence from focus schools in Kentucky.

Under waivers to the No Child Left Behind (NCLB) Act, the federal government required states to identify schools where targeted subgroups of students have the lowest achievement and to implement reforms in these “Focus Schools.” In this study, we examine the Focus School reforms in the state of Kentucky. The reforms in this state are uniquely interesting for several reasons. One is that the state developed unusually explicit guidance for Focus Schools centered on a comprehensive school-planning process. Second, the state identified Focus Schools using a “super subgroup” measure that combined traditionally low-performing subgroups into an umbrella group. This design feature may have catalyzed broader whole-school reforms and attenuated the incentives to target reform efforts narrowly. Using regression discontinuity designs, we find that these reforms led to substantial improvements in school performance, raising math achievement by 17 percent and reading achievement by 9 percent

A Hybrid Active Filter Using the Backstepping Controller for Harmonic Current Compensation

This document presents a new hybrid combination of filters using passive and active elements because of the generalization in the use of non-linear loads that generate harmonics directly affecting the symmetry of energy transmission systems that influence the functioning of the electricity grid and, consequently, the deterioration of power quality. In this context, active power filters represent one of the best solutions for improving power quality and compensating harmonic currents to get a symmetrical waveform. In addition, given the importance and occupation of the transmission network, it is necessary to control the stability of the system. Traditionally, passive filters were used to improve energy quality, but they have endured problems such as resonance, fixed remuneration, etc. In order to mitigate these problems, a hybrid HAPF active power filter is proposed combining a parallel active filter and a passive filter controlled by a backstepping algorithm strategy. This control strategy is compared with two other methods, namely the classical PI control, and the fuzzy logic control in order to verify the effectiveness and the level of symmetry of the backstepping controller proposed for the HAPF. The proposed backstepping controller inspires the notion of stability in Lyapunov’s sense. This work is carried out to improve the performance of the HAPF by the backstepping command. It perfectly compensates the harmonics according to standards. The results of simulations performed under the Matlab/Simulink environment show the efficiency and robustness of the proposed backstepping controller applied on HAPF, compared to other control methods. The HAPF with the backstepping controller shows a significant decrease in the THD harmonic distortion rate

Motorized cart

Motorized cart is known as an effective tool and timeless that help people carry heavy loads. For farmers, it has an especially vital tool for moving goods. Oil palm farmers typically uses the wheelbarrow to move the oil palm fruit (Figure 10.1). However, there is a lack of equipment that should be further enhanced in capabilities. Motorized carts that seek to add automation to wheelbarrow as it is to help people save manpower while using it. At present, oil palm plantation industry is among the largest in Malaysia. However, in an effort to increase the prestige of the industry to a higher level there are challenges to be faced. Shortage of workers willing to work the farm for harvesting oil palm has given pain to manage oil palm plantations. Many have complained about the difficulty of hiring foreign workers and a high cost. Although there are tools that can be used to collect or transfer the proceeds of oil palm fruits such as carts available. However, these tools still have the disadvantage that requires high manpower to operate. Moreover, it is not suitable for all land surfaces and limited cargo space. Workload and manpower dependence has an impact on farmers' income

Sustainability ranking of desalination plants using Mamdani Fuzzy Logic Inference Systems

As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability

A Political Economy Model of Regulation Explained Through Fuzzy Logics

The basic problem of environmental regulation involves the government trying to induce a polluter to take socially desirable actions, which ostensibly are not in the best interest of the polluter. But the government may not always be able to precisely control the polluter. To further complicate matters the government faces a complex problem of determining exactly what level of pollution is best for society. In reality the government faces pressures from consumers and polluters. There are some important lessons to gather from the analysis of current models of regulation. One is that there are many imperfect links between the legislature and the pollution-generating process. In this case regulation may be excessively costly, may result in considerable cheating, and may result in excessive pollution. Another lesson is that legislature does not necessarily act as an efficient benevolent maximizer of social well-being. The authors intend in this paper to explain the current view of political models of regulation, analysing them for their complexity, and attempt to provide a reasonable explanation of their functioning recurring to fuzzy logics. Understanding how the browns and greens interact with the legislature and regulatory agencies can to some extent explain the current environmental regulations. The fuzzy approach, intends to allow for easier understanding of these interactions, and provide an answer for more effective decision making. Keywords: Environmental Regulation, Environmental Economics, Fuzzy Logics, Models, Pollution Control, Sustainability

Applications of Soft Computing in Mobile and Wireless Communications

Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications