Green Smart Research Articles

An Assessment of the Influence of the Right to a Healthy Environment on the Design of Smart Green Cities

An Assessment of the Influence of the Right to a Healthy Environment on the Design of Smart Green Cities

A power demand resilience analysis of the residential and commercial areas for Fengshan smart green community in Taiwan

As global climate change intensifies, extreme catastrophic weather. As a result, the vulnerability of power infrastructure gradually worsens, leading to an increased threat of power supply disruption. In order to cope with the threat of possible power supply disruption and to accommodate more residents in the event of a disaster, backup power generation and storage facilities are necessary should establish in residential and commercial areas. This study establishes a software analysis model of power demand resilience in the residential area, analyzes various power demand resilience scenarios, and discusses the operation of reasonable backup power generation and energy storage facilities, and power load management and control strategies. In the future, these software tools will be used to analyze the rational allocation and operation strategies of disaster prevention at power facilities in similar situations. This study takes the Fengshan Smart Green Community as the reference field, and extends the simulated facilities as the area of power demand resilience analysis, in an integrated residential area and a commercial area. This study has completed four case studies, including: (1) baseline scenario, (2) “use of diesel generators” scenario, (3) “expanding lithium battery capacity” scenario, and (4) “expanding lithium battery capacity and controlling lithium battery power output in the integrated residential area” scenario. The conclusions of this study include: (1) To cope with the intensified global climate change, adequate deployment of various backup power generation and storage facilities to enhance power resilience can effectively mitigate the threat of power supply disruption. (2) According to the case study results, there is sufficient solar photovoltaic in the residential area of Fengshan Smart Green Community. However, the energy storage and power supply capacity of lithium batteries are insufficient, and it is challenging to perform the backup power function. (3) To supply electricity to the power management system and the medical and shelter area adequately, this study suggests Fengshan Smart Green Community strengthens the power storage and power supply capacity of lithium batteries. (4) Solar photovoltaics are zero-carbon power; it can be a priority backup for power demand resilience. However, solar power is not available when there is insufficient sunshine. (5) The use of a diesel generator can flexibly assist the solar photovoltaic and lithium batteries to ensure the adequate power supply. (6) The use of diesel generators for power generation during a time of crisis is not pollution-free. However, their use for management in a crisis or disaster situation is in order when other power supply backups are insufficient or have failed. The critical findings include: (1) Solar photovoltaics are zero-carbon power; it can be a priority backup for power demand resilience. However, solar power is not available when there is insufficient sunshine. (2) The use of diesel generators for power generation during a time of crisis is not pollution-free. However, their use for management in a crisis or disaster situation is in order when other power supply backups are insufficient or have failed.

Preface

The 10th Greentechnology International ConferenceThe International Conference on Green Technology (ICGT) is an annual scientific meeting organized by Faculty of Science and Technology, State Islamic University (UIN) of Maulana Malik Ibrahim at Malang, East Java, Indonesia. The objective of this conference is to provide a forum eminent professionals, scientists, researchers, academicians and entrepreneurs across the globe to exchange and explore the issues, innovations and integrated perspectives towards environmental sustainability. The theme for 10th ICGT is Empowering the Fourth Industrial Revolution through Green Science and Technology which had been conducted on October 2nd-3rd, 2019 at Savana Hotel and Convention. Several topics have been discussed in this conference such as the following topic areas: biomaterial sciences, environmental impact evaluation, environmental education, human ecology, sustainable environmental technology, green architecture and design, energy and ecological conservation, green smart technology and innovation and soon.The 10th ICGT was attended by the participants not only from Indonesia, foreign countries, such as Thailand, Malaysia, Japan, and Germany. The committee recorded that total number of attendants reached 210 people. There were 176 articles have been submitted to editors of conference for further evaluation and review. After the double review process, finally only 90 papers have been accepted for publication.The success of The of 10th ICGT is due to the effort and support from all parties in this even. Thus, we would like to the scientific ommittee members, organizing committee members, anonymous reviewers, keynote and invited speakers, authors, presenters, and sponsor such as PT Dharma Karya Makmur Sentosa, GeneCraft Labs, Thermoscientific, and all sponsor who contributed to the success of this event.Please let us express our depest condolences for beloved friend, our committee members: Nurvita Maharani (1991-2019) for her contribution arranging the proceeding. This proceeding volume was dedicated for her big effort to make all accepted papers more valuable.Finally, we would also like to thank IOP Publishing Company for their support in publishing The 10th ICGT conference proceedings.List of Editors in chief are available in this pdf.

Implementation of green chemistry principles in circular economy system towards sustainable development goals: Challenges and perspectives.

Green chemistry principles (GCP) are comprehensively deployed in industrial management, governmental policy, educational practice, and technology development around the world. Circular economy always aims to balance the economic growth, resource sustainability, and environmental protection. This article offers a highlight on issues of significance within GCP and circular economy, and proposes the integrated strategies for GCP implementation from the aspects of governance, industry and education. At first, we developed a new categorizing system for GCP dividing to (i) pollution and accident prevention, (ii) safety and resource sustainability, and (iii) energy and resource sustainability. To assess the GCP practice towards the circular economy, the implementation of international movement of GCP in worldwide policy, especially those of Canada, China, Germany, Japan, South Korea, Sweden, Taiwan, United States and United Kingdom were reviewed. The policy implementation of GCP practices among governance, industries and education was analyzed. To integrate GCP into the circular economy concept, we also proposed five strategies of priority governance direction as follows: (i) establishment of cross-departmental collaboration, (ii) development of cleaner production and green product, (iii) provision of integrated chemical management system, (iv) implementation of green chemistry education program, and (v) construction of a business model. Finally, we discussed the prospects of disciplinary elements including the establishment of redesign-reduction-recovery-recycle-reuse (5R) practices for wastes reclamation, deployment of water-energy-food nexus with GCP to improve the food security and resource sustainability, and implementation of GCP in the green smart industrial park.

Smart Green House Gas Footprint Display with Integrated Smart Power Monitoring and IoT Actuation

This research paper is about a one-for-all device that has a central synchronization with a Wireless Sensor Network connected to other part of the house. This network can do an all-round power saving and environment awareness tasks. The device takes power consumption readings from the mains, and displays the Greenhouse gas (GHG) emissions and footprint of the users in a particular time frame along with the current electricity bill. The WSN mainly focuses on Kitchen, Bathrooms and AC rooms. A certain toxic amount of Carbon Monoxide gas is produced from burning of stoves in Kitchen. During cooking, a gas sensor (MQ7) is placed in the kitchen measures the amount of different gases, especially CO. Chimney is turned on only when CO reading crosses a certain threshold. In this way, power consumed by chimney can be reduced markedly. Similarly in the water tanks above the house, a water temperature sensor is placed. This sensor allows the intensity of the water heater to be automatically regulated depending on the temperature of water in the tank. If water is already at the user-required temperature, the water heater is adaptively changed to a lower temperature or switched off, so as to consume less power. The third sensor is placed in an AC room. Even the high star-rated ACs are a major concern in power consumption, electricity bill and GHG emissions. Hence the temperature sensor is placed which measures the room temperature and outdoor temperature. If it is cold enough, the AC switches-off, thereby saving unnecessary power consumption.

Welcome to the exciting world of “Green Computing and Smart Environments”

Welcome to the exciting world of “Green Computing and Smart Environments”

Integrated Intelligent Green Scheduling of Predictive Maintenance for Complex Equipment based on Information Services

As an important link to guarantee normal industrial production, equipment maintenance plays an increasingly key role in enhancing the competitiveness of enterprises and supporting green smart manufacturing. This paper aims to promote the implementation of predictive maintenance for complex equipment and improve the green performance of the maintenance service process. A structural framework of information sharing and service network is introduced to build a ubiquitous state data awareness environment for predictive maintenance service. Subsequently, an integrated mathematical problem model that consists of carbon emission objective and extended maintenance cost objective is constructed. Then an improved NSGA-II algorithm is utilized to solve this complicated two-objective optimization problem. In response to deal with the uncertainties of maintenance service environment and inaccuracy of prediction, a data-driven dynamic adjustment strategy is applied. A grinding roll fault case of a large vertical is used to demonstrate the effectiveness of this proposed approach.

Smart Green Bridge - Wildlife Crossing Bridges of New Generation

The research content of the paper is focused on landscape-vegetation and technical-economic optimization of vegetation elements of buildings. The length of the motorway in the Czech Republic has increased approximately three times since 1995. Road transport infrastructure is constantly growing. Ensuring the passage of important transport structures for fauna is an objective requirement. The function of migration corridors is ensured by wildlife crossing bridge. These constructions are currently based on concrete and steel, which is not only environmentally friendly but also presents several other problems. The paper presents the idea of a new smart solution for wildlife crossing bridge. Smart Green Bridge is based on principles and technologies following the sustainable development such as the use of load-bearing timber structures, extensive greenery of about 100 mm thickness, vertical greenery, self-guiding vertical and horizontal irrigation systems, photovoltaic panels, battery energy storage and next.

Blockchain Based Connected Vehicles for Smart Green City Environment

Air pollution is perceived as a modern-day curse, a fatal by-product of increasing urbanization and rapid industrialization. The phenomenon has a plethora of negative impacts, including human health issues, damage to ecosystems, decreasing quality of food crops, and abatement of environmental standards. Passenger vehicles are a major contributor to air pollution, producing significant amounts of nitrogen oxides and carbon monoxide, among other pollutants. It is therefore necessary to enforce greener practices among citizens and introduce a reliable mechanism that encourages responsible behavior to support the environmental cause. The proposed work aims to circumvent the aforementioned problem with an IoT-enabled solution powered by blockchain technology to foster environment friendly practices in registered vehicle owners. The real essence of this project is to leverage technological innovations to solve pollution issues that befoul the urban atmosphere. We seek to achieve this goal with a financial reward-penalty scheme that drives the urban populace to practice green living, while monitoring pollution levels using an IoT device. The ability of blockchain networks to provide a verifiable record of actions and violations [1], coupled with the capabilities of Internet of Things (IoT) paradigms to detect pollution levels present in vehicular exhaust, is exploited in this project.

Distributed modeling of smart parking system using LSTM with stochastic periodic predictions

Parking in contemporary cities is a time- and fuel-consuming process. It affects daily stress levels of drivers and citizens. To design the future cities, parking process should be handled efficiently to improve drivers’ time comfort and fuel economy toward a green smart city (SC) ecosystem. In this paper, we propose to model smart parking (SP) with multiagent system (MAS) using long short-term memory (LSTM) neural network. Our model outperforms similar approaches as evidenced from the presented results using an online dataset from the SC of Aarhus, Denmark. We use LSTM for stochastic prediction based on periodic data provided by parking sensors. A SP provides such data on daily basis over a short period of time in the SC. We evaluate the proposed MAS with the prediction accuracy metric and compare it with other approaches in the literature. The proposed system achieves higher prediction accuracy per daily basis than the compared approaches due to our stochastic periodic prediction design and input to the proposed MAS and LSTM model. In addition, LSTM is used more efficiently under the proposed architecture of MAS, which enables online scaling thanks to dynamic and distributed nature of MAS.

Experimental Analysis of Smart Green House with Rotary Garden

To overcome climate change that affects agriculture in all over the world, shows the estate and farming for the raising of the extreme weather (e.g., floods, droughts, etc). Therefore, the smart greenhouse is essential in providing sustainable food for humans. The application of Smart Greenhouse, The ultimate and most common monitored variables are temperature, moisture, the intensity of sunlight and environmental conditions to support the using of sunlight a source of electricity. This is necessary for the Smart Greenhouse to manipulates the environment in appropriate to its plant’s needs. In this case, the temperature and humidity in the greenhouse are important to keeps the productivity of the plants. So, it’s using automatic system to keep suitable environmental conditions as explained before for the plants. In this research, the smart Greenhouses is shaped Ferris wheel to make sprinkling and radiation of sunlight for plants is equally distributed for all plants and its parts, Based on the results of this experiments with rotary mechanical system for Smart Greenhouse as well shown that Smart Greenhouse can preserve suitable temperature and moisture for growing the plants.

INTELLIGENT ROOFTOP GREENHOUSES AND GREEN SKYLINE CITIES

The paper proposes a new concept of green building, able to oppose the global warming, the Intelligent Rooftop Greenhouse iRTG, as a development of the Integrated Rooftop Greenhouse IRTG. Our approach is to re­place conventional roofs with IRTGs, which are constructively con­nected with the interior of the building by flows of energy, gazes (mainly O2 enriched air from RTG to building and CO2 enriched air from build­ing to RTG) and water in order to improve the building’s metabolism. A tight human-plant sym­biosis is created such way. iRTGs perfect this architecture by actively controlling the energy, gazes and water flows, by collecting the available renewable energy resources (geothermal, sun, wind) and by adding Internet of Things IOT features to the system, in order to connect it to a surrounding Smart City. This way iRTGs may achieve an efficient integrated management of energy, gases and water, using just existing technologies: heat pumps (water to water for building’s basement and air to air for green­house), solar panels, IOT equipment, etc., controlled in a smart/intelligent manner. If a Smart City is composed mostly of iRTG buildings it becomes a Smart Green Skyline City, with low carbon foot­print and high carbon offset. The paper provides a mathematical iRTG model.

Accelerating the construction of natural gas system engineering in green smart cities

Accelerating the construction of natural gas system engineering in green smart cities

An Energy-Efficient Elevator Operating System that Considers Sensor Information and Electricity Price Changes in Smart Green Buildings

In modern smart buildings, the energy consumption of a building is monitored every time. Smart buildings are also equipped with sensors that can collect various physical data such as temperature, motion, and light. In this paper, we use smart sensor technologies in the design of an efficient elevator operating system (EOS). Specifically, multiple sensor devices are used together to detect elevator passengers’ behavior before they arrive at the elevator door and press the elevator call button. The detected information is then delivered to EOS through building networks and the scheduling system utilizes this information for the efficient control of the elevator cars. Specifically, when the number of passengers becomes large, EOS increases the number of working elevator cars to reduce the waiting time of passengers. In contrast, when the elevator traffic lessens, EOS reduces the number of working elevator cars in order to save the energy consumption. Experimental results with a wide range of configurations show that our EOS outperforms the conventional elevator scheduling system that does not consider sensor information or electricity price changes.

Editorial: IEEE Transactions on Sustainable Computing, Special Issue on Secure Sustainable Green Smart Computing

The booming development of cloud computing has resulted in a remarkable growth of multiple industries in which dramatic demands of green computing and sustainability are addressed. The platform of smart computing has provided an efficient approach for connecting various infrastructure such that many new technologies are eventually formed, such as Internet-of-Thing and ubiquitous computing. The concept of sustainable green smart computing has become a significant issue for those enterprises or practitioners who are engaging the implementations of smart computing aiming at a longer-term strategy. Considering the achievement of the real sustainability, one of the crucial values is to ensure all operations across different computing sources are under a secure executive environment. For reaching a high performance of securing sustainable green smart computing, many problems need to be solved. For example, one of the main challenges is to balance the costs among security, energy, performance, and sustainable requirements. The distribution of the computing resources in this issue is a great challenge because the real-time executions are usually constrained by multiple elements. An efficient approach of providing an adaptive and scalable service as well as addressing sustainability is an urgent research direction for current advanced cloud computing applications. Thus, this special issue aims at collecting updated outstanding papers that illustrate the latest achievements and development updates concerning the security solutions, issues, applications, trends, and implementations in sustainable green smart computing.

Analysis of a Survey on Public Perceptions and Preferences of the “Smart Green Office” to Help Encourage Creation of the Program

Analysis of a Survey on Public Perceptions and Preferences of the “Smart Green Office” to Help Encourage Creation of the Program

Green Smart Technology for Water (GST4Water): Water Loss Identification at User Level by Using Smart Metering Systems

A real-time household water consumption monitoring and processing system aimed at leakage identification at user level is presented here. The system, developed within the GST4Water project, allows consumption data sent by a generic smart meter installed in a user’s house to be received and transferred to a cloud platform. Here, the consumption data are stored and processed through an empirical algorithm able to automatically identify leakage at the individual user level by looking for non-consumption in certain periods of the day. With reference to a real-life case study, the results obtained show that the algorithm enables leakages on users’ properties to be identified with an accuracy of more than 90%. Therefore, the implementation of this algorithm within a highly innovative smart metering system can represent an efficient tool for reducing water losses at user level.

Green Smart Technology for Water (GST4Water): Life Cycle Analysis of Urban Water Consumption

The increasing scarcity of water is encouraging strategies in water saving and urban water management systems devoted to reducing natural resource consumption and environmental impact. At household and urban scales, there is an increasing interest in onsite greywater and non-potable water reuse systems in order to improve water availability. In this framework, the project GST4Water funded by the European Union (EU) under the POR-FESR 2014–2020 Program of Emilia-Romagna Region, has been developed with the aim to implement water consumption monitoring systems, to define solutions for greywater reuse, and to develop tools for environmental sustainability evaluation applied to water systems. The present study focuses on this last goal, performing a life cycle assessment of the solutions optimized at a district level. In particular, six different scenarios are compared, starting from two models considering traditional water supply together with or without energy consumption related to hot water generation, and five additional models related with different assumptions in terms of greywater recovery systems, and energy and hot water production, at varying percentages of renewable and photovoltaic energy supply. Finally, an evaluation of the return time of environmental investment is carried out, based on the results obtained through the scenario analysis.

Towards an optimal resource management for IoT based Green and sustainable smart cities

Internet of Things (IoT) is an emerging technology for the smart city that interconnects various digital devices through Internet, hence, providing multiple innovative facilities from academia to industry and healthcare to business. Smart city is the ubiquitous and a paradigm shift which has revolutionized the entire landscape with the support of information and communication technology (ICT), sensor-enabled IoT devices. For the better and big picture of the entire scenarios with high visibility multimedia (i.e., video, audio, text, and images) transmission is the soul-concept in the smart world, but due to resource-constrained (power hungry and limited battery lifetime) nature of these tiny devices (which are building blocks of smart city) and voluminous amount of the data it is very challenging to openly talk about the sustainable and Green smart city platform. Thus, to remedy these problems two Hybrid Adaptive Bandwidth and Power Algorithm (HABPA), and Delay-tolerant Streaming Algorithm (DSA) are proposed by adopting stored video stream titled, StarWarsIV. Besides, a novel architecture of smart city system is proposed. Experimental results are obtained and analyzed in terms of performance metrics i.e., power drain, battery lifetime, delay, standard deviation and packet loss ratio (PLR) in association to the buffer size. It is concluded that the HABPA (45%,37%,20 ms) significantly optimizes power drain, battery lifetime (37%), standard deviation (3.5 dB), PLR (4.5%) of the IoT-enabled devices with less delay than DSA (43%, 32%,25 ms, 5 dB, 5.75%) and Baseline (42%,28%, 30 ms, 6 dB, 6.53%) respectively during media transmission in smart city.

Big-data analysis for carbon emission reduction from cars: Towards walkable green smart community

To achieve low carbon cities or green smart city, it is very important to foresee how we can reduce the number of cars in the residential communities without losing convenience and comfort of people. For that purpose, walkability is one of the key performance indicators expressing the environmental quality of a district. As the first step for creating a low-carbon smart community, this study attempts to evaluate the influence of walkability on traffic behavior of people by using mobile GPS data. Specifically, we statistically analyze the relationship between various walkability indices (centrality, betweenness, angularity, etc.) evaluated by road network data, and pedestrian movement estimated by mobile GPS data in the six main wards in Tokyo, Japan. The result suggests the usefulness of our approach for low-carbon smart community design rousing people’s walking activity. The walkability results and data are then compared to the results of a macrosimulation traffic model for the Sumida Ward of Tokyo to understand the impact that walkability may have on emissions if built environment conditions are improved in favor of a lesser automobile mode share.