Internet of things

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things(IoT)emergedasaholisticproposaltoenableanecosystemofvaried,heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing today’s pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efficient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identified synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth

Opportunities and challenges of geospatial analysis for promoting urban livability in the era of big data and machine learning

Urban systems involve a multitude of closely intertwined components, which are more measurable than before due to new sensors, data collection, and spatio-temporal analysis methods. Turning these data into knowledge to facilitate planning efforts in addressing current challenges of urban complex systems requires advanced interdisciplinary analysis methods, such as urban informatics or urban data science. Yet, by applying a purely data-driven approach, it is too easy to get lost in the ‘forest’ of data, and to miss the ‘trees’ of successful, livable cities that are the ultimate aim of urban planning. This paper assesses how geospatial data, and urban analysis, using a mixed methods approach, can help to better understand urban dynamics and human behavior, and how it can assist planning efforts to improve livability. Based on reviewing state-of-the-art research the paper goes one step further and also addresses the potential as well as limitations of new data sources in urban analytics to get a better overview of the whole ‘forest’ of these new data sources and analysis methods. The main discussion revolves around the reliability of using big data from social media platforms or sensors, and how information can be extracted from massive amounts of data through novel analysis methods, such as machine learning, for better-informed decision making aiming at urban livability improvement

Multi-sensory Integration for a digital earth nervous system

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.The amount of geospatial data is increasing, but interoperability issues hinder integrated discovery, view and analysis. This paper suggests an illustrative and extensible solution to some of the underlying challenges, by extending a previously suggested Digital Earth Nervous System with multi-sensory integration capacities. In doing so, it proposes the combination of multiple ways of sensing our environment with a memory for storing relevant data sets and integration methods for extracting valuable information out of the rich inputs. Potential building blocks for the implementation of such an advanced nervous system are sketched and briefly analysed. The paper stimulates more detailed considerations by concluding with challenges for future research and requesting a multidisciplinary development approach – including computer sciences, environmental sciences, cognitive and neurosciences, as well as engineering

Multi-sensory Integration for a Digital Earth Nervous System

The amount of geospatial data is increasing, but interoperability issues hinder integrated discovery, view and analysis. This paper suggests an illustrative and extensible solution to some of the underlying challenges, by extending a previously suggested Digital Earth Nervous System with multi-sensory integration capacities. In doing so, it proposes the combination of multiple ways of sensing our environment with a memory for storing relevant data sets and integration methods for extracting valuable information out of the rich inputs. Potential building blocks for the implementation of such an advanced nervous system are sketched and briefly analysed. The paper stimulates more detailed considerations by concluding with challenges for future research and requesting a multidisciplinary development approach – including computer sciences, environmental sciences, cognitive and neurosciences, as well as engineering.JRC.H.6-Digital Earth and Reference Dat