Evaluation of concrete corrosion using EMI sensor

Reinforced Concrete (RC) is globally used to make the building structure strong and more durable. Civil and structural engineers face major challenges as concrete structures deteriorate and get weaker. Recent development in field of assessing and monitoring the health condition of the building structure have shown that corrosion in concrete reinforcement is the cause of failure. Thus, there lies a better research opportunity in the field of monitoring and assessing health condition of the building structure. This paper presents an innovative technique of initial monitoring of corrosion in concrete structures using Non-Destruction Evaluation (NDE). An early monitoring sensor was developed using Faradays law of electromagnetic induction (EMI) principle, multiple loop coil (MLC) acts a sensor which has a receiver and transmitter coil. The placement of the two coils on concrete structures measures the potential difference which later is used to analyse the level of corrosion

Pressure simulation for footstep energy harvesting paver

Amongst all the energy sources from human motion, footstep has the potential of producing electrical energy as an alternative source to non-conventional renewable energy. Researchers have shown that human footstep kinetic energy can be converted to electrical energy by devised mechanism for low power application such as powering lights, radio and charging phones. Eventually, a novel fluid based energy harvesting paver was developed and tested to contribute towards sustainable development. The paver uses mini hydro generators to produce energy as fluid is forced through these mini hydro generators upon human stepping. This paper presents the pressure simulation of fluid bag system when subjected to an applied human force and the quarter ellipsoid shaped proved to be the best performer which can produce upto 1.4J per step. The pressure simulation provides a relation between pressure and output power

Distributed energy resources and the application of AI, IoT, and blockchain in smart grids

Smart grid (SG), an evolving concept in the modern power infrastructure, enables the two-way flow of electricity and data between the peers within the electricity system networks (ESN) and its clusters. The self-healing capabilities of SG allow the peers to become active partakers in ESN. In general, the SG is intended to replace the fossil fuel-rich conventional grid with the distributed energy resources (DER) and pools numerous existing and emerging know-hows like information and digital communications technologies together to manage countless operations. With this, the SG will able to “detect, react, and pro-act” to changes in usage and address multiple issues, thereby ensuring timely grid operations. However, the “detect, react, and pro-act” features in DER-based SG can only be accomplished at the fullest level with the use of technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and the Blockchain (BC). The techniques associated with AI include fuzzy logic, knowledge-based systems, and neural networks. They have brought advances in controlling DER-based SG. The IoT and BC have also enabled various services like data sensing, data storage, secured, transparent, and traceable digital transactions among ESN peers and its clusters. These promising technologies have gone through fast technological evolution in the past decade, and their applications have increased rapidly in ESN. Hence, this study discusses the SG and applications of AI, IoT, and BC. First, a comprehensive survey of the DER, power electronics components and their control, electric vehicles (EVs) as load components, and communication and cybersecurity issues are carried out. Second, the role played by AI-based analytics, IoT components along with energy internet architecture, and the BC assistance in improving SG services are thoroughly discussed. This study revealed that AI, IoT, and BC provide automated services to peers by monitoring real-time information about the ESN, thereby enhancing reliability, availability, resilience, stability, security, and sustainability

Prevalence and associated risk factors for mental health problems among young adults in Fiji Island during COVID-19: a cross-sectional study

IntroductionThe COVID-19 pandemic has had a significant impact on mental health globally. To understand the impact of the pandemic on mental health in Fiji, this study aimed to investigate the prevalence of anxiety disorder and depression among the young adults.MethodAn online survey was conducted to assess the prevalence of anxiety disorder and depression among the general population in Suva, Fiji during the COVID-19 pandemic. A total of 1,119 Fiji adults participated in the study. The study was conducted between May 20 to June 30, 2022, using a snowball sampling via social media platforms. The Generalized Anxiety Disorder (GAD-7) and Patient Health Questionnaire (PHQ-9) scales were used to measure anxiety and depression, respectively. The COVID-19 related stressors was evaluated using the adapted SARS stressors assessment. Univariate and multivariate logistic regression analysis was performed to determine the factors influencing mental health among respondents.ResultsThe result shows that a significant portion of individuals experienced each of the stressors, with the highest prevalence seen for hearing information about the severity of COVID-19. The prevalence of anxiety and depression was found to be 45% and 49%, respectively. Being female, having pre-existing illness and COVID-19 stressors were a risk factor to develop anxiety and depression. On the other hand, employed individuals and having high BMI was a protective factor against developing depression during COVID-19 lockdown.ConclusionThese findings highlight the importance of addressing the mental health needs of the Fijian population during the COVID-19 pandemic and beyond

Systematic categorization of optimization strategies for virtual power plants

Due to the rapid growth in power consumption of domestic and industrial appliances, distributed energy generation units face difficulties in supplying power efficiently. The integration of distributed energy resources (DERs) and energy storage systems (ESSs) provides a solution to these problems using appropriate management schemes to achieve optimal operation. Furthermore, to lessen the uncertainties of distributed energy management systems, a decentralized energy management system named virtual power plant (VPP) plays a significant role. This paper presents a comprehensive review of 65 existing different VPP optimization models, techniques, and algorithms based on their system configuration, parameters, and control schemes. Moreover, the paper categorizes the discussed optimization techniques into seven different types, namely conventional technique, offering model, intelligent technique, price-based unit commitment (PBUC) model, optimal bidding, stochastic technique, and linear programming, to underline the commercial and technical efficacy of VPP at day-ahead scheduling at the electricity market. The uncertainties of market prices, load demand, and power distribution in the VPP system are mentioned and analyzed to maximize the system profits with minimum cost. The outcome of the systematic categorization is believed to be a base for future endeavors in the field of VPP development

Design and analysis of photovoltaic powered battery - operated computer vision - based multi - purpose smart farming robot

Farm machinery like water sprinklers (WS) and pesticide sprayers (PS) are becoming quite popular in the agricultural sector. The WS and PS are two distinct types of machinery, mostly powered using conventional energy sources. In recent times, the battery and solar-powered WS and PS have also emerged. With the current WS and PS, the main drawback is the lack of intelligence on water and pesticide use decisions and autonomous control. This paper proposes a novel multi-purpose smart farming robot (MpSFR) that handles both water sprinkling and pesticide spraying. The MpSFR is a photovoltaic (PV) powered battery-operated internet of things (IoT) and computer vision (CV) based robot that helps in automating the watering and spraying process. Firstly, the PV-powered battery-operated autonomous MpSFR equipped with a storage tank for water and pesticide drove with a programmed pumping device is engineered. The sprinkling and spraying mechanisms are made fully automatic with a programmed pattern that utilizes IoT sensors and CV to continuously monitor the soil moisture and the plant’s health based on pests. Two servo motors accomplish the horizontal and vertical orientation of the spraying nozzle. We provided an option to remotely switch the sprayer to spray either water or pesticide using an infrared device, i.e., within a 5-m range. Secondly, the operation of the developed MpSFR is experimentally verified in the test farm. The field test’s observed results include the solar power profile, battery charging, and discharging conditions. The results show that the MpSFR operates effectively, and decisions on water use and pesticide are automated

Adoption of grid - tie solar system at residential scale

Traditionally, remote and urban communities worldwide have been supplied electricity almost completely by fossil fuel generators to accommodate for electricity needs. Currently, the integration of renewable energy sources (RESs) into the current power generation systems can offer attractive economic and environmental merits, including considerable fuel savings and carbon dioxide emission reductions. In relation to sustainability, efficiency and economic feasibility, solar photovoltaic (PV) is one of the most promising sources of RESs which is being touted as a leading solution to long-term electrification and development problems in rural and urban parts of Pacific Island Countries (PICs). In this work, a grid-tie PV system is instigated at a residential scale. The idea of this research is not to claim the power output from the PV system but to show the feasibility of a grid-tie system at a residential scale. This will help the PICs, non-profit organisations and the government better share scarce resources towards achieving their energy goals and be in line with Sustainable Development Goal (SDG) 7, ensuring access to affordable, reliable, sustainable and modern energy for all

Design simulation of a novel fluid based footstep energy harvesting system

With the ever-increasing demand for energy and a growing concern for the non-renewability of the energy sources as well as the environmental pollution, renewable energy harvesting systems have emerged as one of the energy technologies globally. In this context, this research work addresses a novel, clean and environmentally friendly renewable energy generation technology that harvests energy from human locomotion, like walking and running. The developed system is based on two square sized tiles structure paver in which two fluid bags are connected through flow control mechanisms including unidirectional valves and mini hydro generators that convert the human kinetic energy into electricity via fluid movements. All the design related simulations were performed in ANSYS software to find out the optimal parameters like fluid velocity, power output and fluid bag shape etc. Sequentially, it was experimentally observed that the energy harvesting paver can produce an average output power of 1.4 W per step during typical human walking and can power up a DC load of 390 Ω LED. The system is easily reproducible and can be installed with relative ease to power up street lamps, billboards and emergency lighting systems etc. Furthermore, the system is eco-friendly and cost-effective in comparison to other available energy harvesting paver systems. Hence, this novel fluid based footstep energy harvesting paver has considerable prospects as an effective renewable energy system

Build_Eco, Planet Care in Play: Educational Toys

One of the biggest global challenges is the ability to separate the level of materials consumed from the growth of the economy. Consequently economic growth is linked to increased waste generated across the planet. Waste management warrants the attention of passionate and co-creative design by people from different levels of living standards. With rural residents seeking the better lifestyle of their urban counterpart’s, the United Nations estimates that 80% of South Africa’s population will be urbanised by 2050. Poverty in apartheid era townships, inner cities and informal settlements is visibly growing an existing divide between poorer communities and households that generate the bulk of waste in South Africa. The measurement of waste management performance is an important first step as highlighted South Africa’s state of waste report (first draft) 2018. Forty two million tons of waste is produced annually and only 11% is recycled This quote summarises the challenge: “... Narrow the gaps. Bridge the divides. Rebuild trust by bringing people together around common goals. Unity is our path. Our future depends on it,” Antonio Guterres, Secretary-General of the United Nations. Build-Eco, a social-entrepreneurial business dedicated to creating educational toys from waste materials. The driving goal is to implement a global opportunity in response to a global problem. With plastic packaging responsible for 40% of plastic waste, it has a serious impact on environmental health and safety across eco-systems. With minimal capital outlay Clean-Ups is a product that provides a bridge between lifestyles across communities. A home industry well suited to individuals seeking self employment opportunities where they can use their hands and don’t have to incur expensive equipment and machinery costs. Ideal for youth, women, immigrants and other marginalised members of communities. With cleaning materials, glue, nontoxic paints, plastic household waste and plastic medication like containers; a business is possible. A key risk is the “quality” locus of control and people skills of each person joining the industry hub. The overall business is scalable and whilst theoretical viable, should be tested through a small scale pilot. The target market is more affluent members of society including young parents, grandparents and business care givers of children that actively invest in useful, educational toys. These care givers want to give children access to classic proven toys, which contribute to caring for the planet

Improving Overall Equipment Effectiveness by Enabling Autonomous Maintenance Pillar for Integrated Work Systems

Integrated Work System (IWS) and Overall Equipment Effectiveness (OEE) are two popular approaches used by production firms to identify and eliminate production losses. In a highly competitive business environment, companies must increase their efficiency in the manufacturing process to support resilient business continuity. While OEE is widely used as a quantitative tool for measuring the performance of total productive maintenance (TPM), the IWS approach integrates equipment, processes, and involvement of people into a unified approach to reduce costs, improve quality, and increase productivity. Principally, there is an alignment between the two concepts. The IWS has the potential to maximize OEE to eliminate equipment failure and defects, minimize downtime, and maximize productivity with less time, effort, and waste. The purpose of this work is to compare the performance of the OEE with the implementation of the IWS pillar, i.e., autonomous maintenance (AM). The rollout of the AM pillar was carried out on the two identical packaging machines (HLP1) with a speed of 120 packets per minute. The data which is shown in this paper is for both machines during the operational hours. Finally, the analysis showed positive results for both machines within a five-month period, with an increase of 27% and 15% in OEE, respectively. Later in the discussion, the root cause and SWOT analysis were perused for OEE and TPM, respectively, in this paper