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MOOC
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MOOC
Cities are becoming the predominant living and working environment of humanity, and for this reason, livability or quality of life in the city has become crucial. This urban planning course will focus on four areas that directly affect livability in a city: Urban energy, urban climate, urban ecology and urban mobility. The course begins by presenting measurable criteria for the assessment of livability, and how to positively influence the design of cities towards greater livability. We will focus on this basic topic of the human habitat in a holistic way, and introduce possibilities of participatory urban design by citizens, leading towards the development of a citizen design science. You will be able to share your experiences with the other participants in the course and also with the experts from the teaching team. In completing this course, you will better understand how to make a city more livable by going beyond the physical appearance and by focusing on different properties and impact factors of the urban system. Livability in Future Cities is the second course in a series of MOOCs under the title “Future Cities.” This series aims to bring the latest research on planning, managing and transforming cities to places where this knowledge has the highest benefit for its citizens. “Future Cities” provided an overview, and this course will focus on livability in existing and new cities.
- Subjects:
- Building Services Engineering and Building and Real Estate
- Keywords:
- Smart cities Urban ecology (Sociology) Cities towns -- Effect of technological innovations on Quality of life City planning
- Resource Type:
- MOOC
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MOOC
Cities are first and foremost built for people, and in today’s world, people produce large amounts of valuable data, thus contributing to what we call “smart cities." As almost every building and every city is a prototype, these communities are in the early stage of development and require specific attention and expertise as we advance. Smart cities, such as Zurich and Boston, consist of human-made structures or environments that are, in some capacity, monitored, metered, networked and controlled. With this functionality, combined with stationary sensors and mobile devices, data and information have become the new building materials of future cities. Using this data, citizens are now beginning to influence the design of future cities and the re-design of existing ones. In this architecture course, you will learn the basics of information cities and urban science research, as well as how dynamic behavior and citizen-driven learning differentiate the responsive city from the smart city. The cities we present and develop in this course use the stocks and flows of information as the main drivers of change. To deepen your knowledge of smart cities and give a perspective on the future of these cities, we also introduce the concept of citizen design science, a combination of citizen science, urban design, and cognitive design computing. Participants will furthermore have unique access to a design research platform for citizen design science. The intelligent use of data and information is at the core of this course, and these concepts will be the next generation of participatory design and design computing environments.
- Subjects:
- Building Services Engineering and Building and Real Estate
- Keywords:
- Smart cities Cities towns -- Effect of technological innovations on City planning
- Resource Type:
- MOOC
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MOOC
Engineers in the automotive industry are required to understand basic safety concepts. With increasing worldwide efforts to develop connected and self-driving vehicles, traffic safety is facing huge new challenges. This course is for students or professionals who have a bachelor's degree in mechanical engineering or similar and who are interested in a future in the vehicle industry or in road design and traffic engineering. It's also of value for people already working in these areas who wantbetter insight into safety issues. This course teaches the fundamentals of active safety (systems for avoiding crashes or reducing crash consequences) as well as passive safety (systems for avoiding or reducing injuries). Key concepts include in-crash protective systems, collision avoidance, and safe automated driving. The course will introduce scientific and engineering methodologies that are used in the development and assessment of traffic safety and vehicle safety. This includes methods to study the different components of real-world traffic systems with the goal to identify and understand safety problems and hazards. It includes methods to investigate the attitudes and behavior of drivers and other road users as well as recent solutions to improve active safety. Italso includes methods to study human body tolerance to impact and solutions to minimize the injury risk in crashes. Study topics include crash data analysis and in-situ observational studies of drivers and other road users by the use of instrumented vehicles and roadside camera systems. Solutions in active safety, such as driver alertness monitoring, driver information as well as collision avoidance and collision mitigation systems, will be described. Examples of in-crash protective systems are combinations of traditional restraints such as seat belts and airbags but with advanced functions such as automatic adaption to the individual occupant as well as pre-collision activation based on advanced integrated sensor systems and communication systems. The course will be based on recorded lectures that use videos and animations to enhance the experience. Online tutorials that access simulation models will give the participants an experience of influencing parameters in active safety and passive safety systems. As a result of support from MathWorks, students will be granted access to MATLAB/Simulink for the duration of the course.
- Subjects:
- Transportation
- Keywords:
- Traffic safety Roads -- Design construction Motor vehicles -- Safety measures Automobile industry trade
- Resource Type:
- MOOC
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MOOC
This course looks at how increasing greenhouse gases are warming the climate and what it means to decarbonise - reduce the greenhouse gas intensity of - the power sector. It will also provide a range of arguments in favour of decarbonisation, including consideration of ease of access to a secure and affordable energy supply and improvements to health and the environment. This course gathers together information about these different motivating factors for building a lower carbon power sector in one place, and includes a careful consideration of the importance of the political context. This course will challenge you to critically analyse your own political context. We would welcome advisors to senior decision makers in government, civil society activists and others interested in understanding and promoting renewable electricity to take this course. This course will help you develop a better understanding of the different dimensions of a move towards a cleaner power sector and develop more nuanced and detailed arguments.
- Subjects:
- Environmental Engineering and Environmental Policy and Planning
- Keywords:
- Renewable energy sources Energy policy Greenhouse gases -- Prevention Climatic changes
- Resource Type:
- MOOC
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MOOC
Autonomous vehicles, such as self-driving cars, rely critically on an accurate perception of their environment. In this course, we will teach you the fundamentals of multi-object tracking for automotive systems. Key components include the description and understanding of common sensors and motion models, principles underlying filters that can handle varying number of objects, and a selection of the main multi-object tracking (MOT) filters. The course builds and expands on concepts and ideas introduced in CHM013x: ""Sensor fusion and nonlinear filtering for automotive systems"". In particular, we study how to localize an unknown number of objects, which implies various interesting challenges. We focus on cameras, laser scanners and radar sensors, which are all commonly used in vehicles, and emphasize on situations where we seek to track nearby pedestrians and vehicles. Still, most of the involved methods are more general and can be used for surveillance or to track, e.g., biological cells, sports athletes or space debris. The course contains a series of videos, quizzes and hands-on assignments where you get to implement several of the most important algorithms. Learn from award-winning and passionate teachers to enhanceyour knowledge at the forefront of research on self-driving vehicles. Chalmers is among the top engineering schools that distinguish itself through its close collaboration with industry.
- Subjects:
- Electrical Engineering, Mechanical Engineering, and Transportation
- Keywords:
- Automobiles -- Design construction Computer vision Automated vehicles
- Resource Type:
- MOOC
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MOOC
In the past few decades, China's cities have experienced a period of rapid development. Great changes have taken place in both urban space and urban life. With the booming of information and communications technology (ICT), ‘Big data’ such as mobile phone signaling, public transportation smart card records and ‘open data’ from commercial websites and government websites jointly promote the formation of the ‘new data environment’, thus providing a novel perspective for a better understanding of what changes have happened or are happening in China’s cities. This course combines both the new data generated for urban analysis and its research applications. The content ranges from big data acquisition, analysis, visualization and applications in the context of China’s urbanization and its city planning, to urban modeling methods and typical models, as well as the emerging trend and potential revolution of big data in urban planning. We have categorized the overall content of this online course into five sections, namely, overview, data, data processing, application, and perspective. The section of overview introduces cities in transition and describe the changing of urban space and urban life in China. The second section lists some commonly used open data and big data in the ‘new data environment’. Then, methods for data acquisition, cleaning and analysis are illustrated in data processing section. To better explain the data analysis method, the fourth part introduces several Chinese research cases to illustrate the application of these methods in urban research. Last but not least, the last section is the most future-oriented one, which is composed of some methodologies and proposals such as Data Augmented Design (DAD) and Big Model. This course, which shares experiences on big data analysis and its research application, will suit those concerning contemporary urbanizing China and its urban planning in the context of information and communication technologies.
- Subjects:
- Building Services Engineering and Building and Real Estate
- Keywords:
- China Cities towns -- Data processing City planning Big data
- Resource Type:
- MOOC
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MOOC
This course provides the tools needed to build a low-carbon power sector around the world. By diving into the perspective of different players in the power sector - from investors through to utilities, regulators and project developers - you will be able to choose the right strategies, policies and other levers needed to incentivise a cleaner power mix in your own context. This course explores the mix of approaches that can create a pro-renewables environment. It explores this from a policy, regulatory and supply-chain perspective and examines the incentives and rules available. Key policies are brought to life through case studies, learning from both success and failure. Key messages of the course include: - Ambitions for renewable electricity must be grounded in technical and financial feasibility - Pro-renewables environments recognise the needs of energy supply chain actors (e.g. project developers, utilities, regulators, electricity customers) and balances pricing, fiscal and financial and wider policies to incentivise and drive deployment - There are multiple ways to encourage deployment of renewables across different scales – these have strengths and weaknesses and must balance rate of deployment, affordability and efficiency of generation - Incentives and rules are a package and can be aligned to deliver affordable, efficient renewable electricity - several real-world examples demonstrate this - Different countries have succeeded and failed in creating pro-renewables environments – demonstrating that while lessons can be used from these experiences, there is no single route to success and the environment must be bespoke to the circumstances of the country. This course should help decision makers across the electricity supply chain, in both the public and private sector, understand what mix of incentives is ideal from their perspective.
- Subjects:
- Environmental Engineering, Building Services Engineering, and Environmental Policy and Planning
- Keywords:
- Electric power distribution -- Environmental aspects Renewable energy sources
- Resource Type:
- MOOC
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MOOC
Wind turbines and solar panels are likely to play a critical role in achieving a low-carbon power sector that helps address climate change and local pollution, resulting from fossil fuel power generation. Because wind and solar power output is weather-dependent, it is variable in nature and somewhat more uncertain than output from conventional fossil fuel generators. It is therefore important to consider how to manage high penetrations of solar and wind so as to maintain electricity system reliability. This introductory course, delivered by Ieading academics from Imperial College London, with technical input and contributions from the National Energy Renewable Lab (Golden, Colorado), will discuss what challenges variable output renewables pose to the achievability of a reliable, stable electricity system, how these challenges can be addressed and at what costs. Its overall objective is to demonstrate that there is already a range of established technologies, policies and operating procedures to achieve a flexible, stable, reliable electricity system with a high penetration of renewables such as wind and solar. The course uses a variety of country and context-specific examples to demonstrate the concepts. Policy makers, regulators, grid operators and investors in renewable electricity will benefit from a solid understanding of these considerations, thereby helping them drive forward the development of a fit-for-purpose clean power system in their own regional context.
- Subjects:
- Environmental Engineering and Building Services Engineering
- Keywords:
- Electric power production Renewable energy sources Electric power distribution
- Resource Type:
- MOOC
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MOOC
The building industry is exploding with data sources that impact the energy performance of the built environment and health and well-being of occupants. Spreadsheets just don’t cut it anymore as the sole analytics tool for professionals in this field. Participating in mainstream data science courses might provide skills such as programming and statistics, however the applied context to buildings is missing, which is the most important part for beginners. This course focuses on the development of data science skills for professionals specifically in the built environment sector. It targets architects, engineers, construction and facilities managers with little or no previous programming experience. An introduction to data science skills is given in the context of the building life cycle phases. Participants will use large, open data sets from the design, construction, and operations of buildings to learn and practice data science techniques. Essentially this course is designed to add new tools and skills to supplement spreadsheets. Major technical topics include data loading, processing, visualization, and basic machine learning using the Python programming language, the Pandas data analytics and sci-kit learn machine learning libraries, and the web-based Colaboratory environment. In addition, the course will provide numerous learning paths for various built environment-related tasks to facilitate further growth.
- Keywords:
- City planning -- Statistical methods Python (Computer program language) Information visualization
- Resource Type:
- MOOC
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MOOC
Why are hybrid vehicles still more common than battery electric ones? Why are electric vehicles still more expensive than conventional or hybrid ones? In this course, you will get the answers to this and much more. While electric motors can improve vehicles regarding performance, energy consumption and emissions, they suffer from high cost and weight of batteries. Smart combinations of electric motors and combustion engines in a hybrid powertrain can combine these strengths with the advantages of combustion engines. This course is aimed at learners with a bachelor's degree or engineers in the automotive industry who need to develop their knowledge about hybridpowertrains. Inthis course, we willexamine different mechanical layouts of hybrid powertrains and how they influence the performance and complexity of the powertrain. Different sizing of powertrains in micro, mild, full hybrids, as well as plug-in hybrids, is also discussed and you'll learn how they can be modelled and analyzed for example by simulation of driving cycles. You will also learn about the Energy Management system and how this controls the hybrid powertrain modes and when to charge and discharge the battery. As a result of support from MathWorks, students will be granted access to MATLAB/Simulink for the duration of the course.
- Subjects:
- Electrical Engineering, Mechanical Engineering, and Transportation
- Keywords:
- Electric vehicles Hybrid electric vehicles
- Resource Type:
- MOOC