A roadmap for China to peak carbon dioxide emissions and achieve a 20% share of non-fossil fuels in primary energy by 2030

As part of its Paris Agreement commitment, China pledged to peak carbon dioxide (CO2) emissions around 2030, striving to peak earlier, and to increase the non-fossil share of primary energy to 20% by 2030. Yet by the end of 2017, China emitted 28% of the world's energy-related CO2 emissions, 76% of which were from coal use. How China can reinvent its energy economy cost-effectively while still achieving its commitments was the focus of a three-year joint research project completed in September 2016. Overall, this analysis found that if China follows a pathway in which it aggressively adopts all cost-effective energy efficiency and CO2 emission reduction technologies while also aggressively moving away from fossil fuels to renewable and other non-fossil resources, it is possible to not only meet its Paris Agreement Nationally Determined Contribution (NDC) commitments, but also to reduce its 2050 CO2 emissions to a level that is 42% below the country's 2010 CO2 emissions. While numerous barriers exist that will need to be addressed through effective policies and programs in order to realize these potential energy use and emissions reductions, there are also significant local environmental (e.g., air quality), national and global environmental (e.g., mitigation of climate change), human health, and other unquantified benefits that will be realized if this pathway is pursued in China

A robot swarm assisting a human fire-fighter

Emergencies in industrial warehouses are a major concern for fire-fighters. The large dimensions, together with the development of dense smoke that drastically reduces visibility, represent major challenges. The GUARDIANS robot swarm is designed to assist fire-fighters in searching a large warehouse. In this paper we discuss the technology developed for a swarm of robots assisting fire-fighters. We explain the swarming algorithms that provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also the means to locate the robots and humans. Thus, the robot swarm is able to provide guidance information to the humans. Together with the fire-fighters we explored how the robot swarm should feed information back to the human fire-fighter. We have designed and experimented with interfaces for presenting swarm-based information to human beings

A Site-Specific Indoor Wireless Propagation Model

In this thesis, we explore the fundamental concepts behind the emerging field of site-specific propagation modeling for wireless communication systems. The first three chapters of background material discuss, respectively, the motivation for this study, the context of the study, and signal behavior and modeling in the predominant wireless propagation environments. A brief survey of existing ray-tracing based site-specific propagation models follows this discussion, leading naturally to the work of new model development undertaken in our thesis project. Following the detailed description of our generalized wireless channel modeling, various interference cases incorporating with this model are thoroughly discussed and results presented at the end of this thesis

Implementación de tecnologías RFID e IoT inalámbricas en el Modelado de información de construcción (BIM)

ABSTRACT: The integration and installation of innovative Radio Frequency Identification (RFID) technologies in combination with wireless Internet of Things (IoT) technologies in Building Information Modelling (BIM), assigned building elements, can create connectivity between the physical- and the virtual world. Beyond the identification of physical objects, further information can be connected, which can be made available to different user groups during the entire life cycle of the building structure. This provides a high level of transparency, in that by scanning the tagged building elements, complete associated information can be accessed and presented to users via applications, in visual and audio form. One use of an RFID and BIM-supported electronic guidance system, namely for the visually impaired, has already been investigated in my bachelor thesis at the University of Applied Sciences (Technische Hochschule Mittelhessen, THM). This Master’s Thesis focuses on the implementation of passive RFID technology into BIM models in combining them with open-source software applications. BIM represents the digital twin of building models in the digital world and can be linked to physical structures (buildings, roads, sewer systems and such others) and building materials (e.g. textiles, mineral and plastic floor coverings, concrete components) by integrating RFID tags. Connecting the parametric BIM models with the physical building elements by using RFID and wireless IoT technologies in a multi-platform application enables the BIM building models to be actively used throughout the life cycle of a building, not only by the facility management, but also by the public for various use cases. During the literature review, suitable software and hardware components were selected, and a prototype multi-platform application for a navigation and positioning system was developed as proof of concept for the Industry Foundation Classes (IFC) file. (See Demo Version at https://opennavibim.herokuapp.com/ ). The challenge was to read the RFID tags in different installation scenarios. Depending on the installation situations (under, over or in the material), various requirements were specified for RFID tags and readers (RFID, handhold personal digital assistant “PDA”). In this field, further hardware developments are necessary.RESUMEN: Mediante la integración e instalación de la innovadora tecnología de identificación por radiofrecuencia (RFID, Radio Frequency Identification) en el modelado digital de información de construcción (BIM, Building Information Modelling), con la interconexión inalámbrica del internet de las cosas (IoT, Internet of Things), es posible crear una conectividad entre el mundo físico y el virtual. Más allá de la mera identificación de objetos existentes, esta conectividad permite incorporar información adicional, que puede ponerse en disposición de los diferentes grupos de usuarios que intervienen durante el ciclo completo de vida de la estructura de la edificación. Se consigue un alto de nivel de transparencia en ese traspaso de información, accesible por medio del escaneado de los elementos etiquetados en la edificación, al tener una completa información asociada que es presentada a los usuarios vía aplicaciones en formato visual o de audio. Una investigación en la aplicación de tecnología RFID basada en BIM para un sistema de navegación electrónica, destinada a personas con discapacidad visual, ha sido desarrollada en mi trabajo fin de grado en la Universidad de Ciencias Aplicadas de Mittelhessen (THM). El presente Trabajo Fin de Master se centra en la implementación de tecnología RFID pasiva en modelos BIM combinados con aplicaciones de software libre. El modelo BIM representa el gemelo digital de los elementos de construcción en el mundo virtual, permitiendo establecer una relación del modelo con estructuras físicas (edificios, carreteras o sistemas de alcantarillado, entre otros) y materiales de construcción (por ejemplo, textiles, cubiertas de suelo minerales o plásticas, componentes de hormigón, …) por medio de la integración de etiquetas RFID. La conexión de los modelos paramétricos BIM con los elementos físicos del edificio, mediante el uso de tecnologías RFID e IoT inalámbricas en una aplicación multiplataforma, permite que los modelos de construcción BIM se utilicen activamente a lo largo del ciclo de vida de un edificio, no solo por la gestión de las instalaciones, sino también por el público para diversos casos de uso. Durante la revisión bibliográfica, se seleccionaron los componentes de software y hardware adecuados, y se desarrolló un prototipo de aplicación multiplataforma para un sistema de navegación y posicionamiento como prueba de viabilidad del concepto del modelo Industry Foundation Classes (IFC). (Véase la versión de demostración en https://opennavibim.herokuapp.com/ ). La lectura de las etiquetas RFID en diferentes en diferentes situaciones de instalación presenta un desafío, dependiendo de la instalación (debajo, encima o en el material) los requisitos impuestos a las etiquetas y lectores RFID son diferentes. Por lo tanto, es necesario seguir desarrollando el hardware en este ámbito.Máster en Ingeniería de Caminos, Canales y Puertos (Plan 2020

Autoencoder extreme learning machine for fingerprint-based positioning: A good weight initialization is decisive

Indoor positioning based on machine-learning (ML) models has attracted widespread interest in the last few years, given its high performance and usability. Supervised, semisupervised, and unsupervised models have thus been widely used in this field, not only to estimate the user position, but also to compress, clean, and denoise fingerprinting datasets. Some scholars have focused on developing, improving, and optimizing ML models to provide accurate solutions to the end user. This article introduces a novel method to initialize the input weights in autoencoder extreme learning machine (AE-ELM), namely factorized input data (FID), which is based on the normalized form of the orthogonal component of the input data. AE-ELM with FID weight initialization is used to efficiently reduce the radio map. Once the dimensionality of the dataset is reduced, we use k -nearest neighbors to perform the position estimation. This research work includes a comparative analysis with several traditional ways to initialize the input weights in AE-ELM, showing that FID provide a significantly better reconstruction error. Finally, we perform an assessment with 13 indoor positioning datasets collected from different buildings and in different countries. We show that the dimensionality of the datasets can be reduced more than 11 times on average, while the positioning error suffers only a small increment of 15% (on average) in comparison to the baseline