The novel approach to creating networks suitable for machine learning systems demonstrated in Artificial Organic Networks will be of interest to academic researchers and graduate students working in areas associated with computational intelligence, intelligent control, systems approximation and complex networks.
He is currently co-founder and CEO at Solarium Labs, the first Mexican research center 100% dedicated to develop intelligent systems for academy and industry. He is also professor and researcher at Tecnológico de Monterrey CCM, Mexico. His main interests are: artificial intelligence, engineering control systems, machine learning, and education.
To cope with utility changes and challenges, many utility companies in India are planning to implement smart grid technology. An SMG system is a subset of a smart electric grid and is generally defined as an intelligent electricity distribution network operating at or below 11 kV and providing electricity to a community. It is supplied by a diverse range of distributed energy resources (DERs), including small, conventional generators such as diesel generators combined with a range of renewable generators such as microhydro, wind turbine, biomass, and solar photovoltaic. SMGs can either be connected to the conventional utility grid or be isolated and provide electricity to a localized load only. An SMG is an application of digital information and communication technology (ICT) and uses advanced sensing, communication, and control technologies to optimize electrical power generation, delivery, and ultimately its end use within the domain of the microgrids. An SMG provides dynamic communication and balancing of the electrical network, thus minimizing losses and increasing the stability of the grid.
HIGHLIGHTSIoT technologies for ambient air quality monitoring were reviewed.IoT platform for ambient air quality management was established.Case studies of pollution monitoring, trace, prevention and improvement were evaluated.Strategies on smart air pollution control could be achieved by A-IoT technologies. ABSTRACTIn order to mitigate the challenges of air pollution, a large number of Internet of Things (IoT)-related technologies have been developed to evaluate and monitor various parameters of air quality. Hence, this paper reviews the fundamental characteristics of IoT; compares and analyzes radio frequency identification (RFID), M2M, and sensor networks; and accordingly proposes an intelligent and multifunctional monitoring platform for reducing air pollution. Our results indicate that establishing systems for comprehensive network communication, cloud-based decision making, information tracking, and online management based on these technologies will improve the ambient air quality more efficiently. Furthermore, we examine several cases verifying the availability and performance of IoT ambient air quality management platforms.
In greater detail, an intelligent air quality monitoring system that embodies flexibility, reliability, effectiveness, and economics (FREE) can be developed by integrating microcontrollers, wireless sensor networks (WSNs), cloud service, the Global Positioning System (GPS), and the Android platform. The Air Benefit and Cost and Attainment Assessment System (ABaCAS; www.abacas-dss.com), which provides decision support tools, including the International Cost Estimate Tool (ICET), Response Surface Model (RSM), Software of Model Attainment Test (SMAT), and Environmental Benefits Mapping and Analysis Program (BenMAP), should be employed during project planning to configure different control scenarios and identify cost-effective strategies. 1e1e36bf2d