Network organization Amsterdam Data Science (ADS) and Elsevier are collaborating together on several fronts, including research and development, joint promotion of Amsterdam as a data science center, and data science talent development. This partnership marks the first long-term collaboration agreement signed by ADS and is interetsed in advancing SDG 9 targets 5, B and C. A number of projects have already started. These are focused on improving data search and reproducibility of research that will ultimately result in higher quality research outcomes.
An autonomous harvester starts to cut robot-grown barley
The groundbreaking Hands Free Hectare project has just seen its first harvest. This £200,000 Innovation UK-funded project by Harper Adams University with Precision Decisions has modified existing machinery to drill, sow, spray and harvest the crop without any human control. The project aims to show how automation can facilitate a sustainable farming system where multiple smaller, lighter machines will enter the field, minimising the level of compaction (SDG 15, life on land and SDG 9, industry, innovation and infrastructure).
The energy performance of buildings draw on a large body of operational data. Applying analytical tools, such as data mining technologies, enables high volumes of data to be examined and applied to be able to make improvements in energy performance. This paper highlights recent advances in the two main data mining tasks in the building field and clearly shows interconnectedness between SDG 11 Sustainable cities and communities and SDG 9 Industry, innovation and infrastructure.
Access to clean and stable energy is a major challenge for many developing African countries. This research aims to investigate ways in which financing renewable energy projects (REPs) can help to address this problem and therefore SDG7. The authors propose the promotion of the two-hand renewable energy service company (ESCO) model as an efficient financial vehicle for increasing sustainable economic development through the production of reliable and stable electricity in semi-urban and rural communities.
Constructing and maintaining transportation infrastructure is very resource intensive and can have negative impacts on the environment. Reviewing geotechnical engineering in transport infrastructure highlights the transformation in the past twenty years to using more sophisticated technologies integrating sustainability principles. SDG target 11.2 aims to provide sustainable transport systems, which this article focuses on, in particular activities relevant to sustainable earthwork construction aimed at minimising the use of energy and production of CO2.
Elsevier,

Environmental Science & Policy, April 2016, Pages 123 - 130

‘Sustainability’ is strategically framed in the context of infrastructure governance in the Netherlands. The open-ended character of sustainability makes it a good discursive concept in governance of large-scale infrastructure projects. This paper discusses some of the implications of the dynamics of sustainability in today’s complex and multi-dimensional world of governance. Prioritising sustainability in infrastructure contributes to the advancement of SDG 9.1 to develop reliable and resilient infrastructure to support economic development and human well-being.
Achieving SDG 11 will require new technologies and innovations to be deployed in the real-estate sector. Already blockchain and artificial intelligence form the foundations of smart buildings, using data on residents' personal preferences to be able to improve efficiency and comfort. This article explores the different technologies and innovations that provide significant untapped potential in the real estate sector.
Elsevier,

Energy and Buildings, Volume 116, 15 March 2016, Pages 703-708

The smart grid's components
Target 11.6 aims to reduce the environmental impact of cities. Technological advances in electric power grid infrastructure, the smart grid, means a greener, more efficient and more adaptable grid. The relationship with the building and the community is explored in this paper to provide a contemporary look at the current state of the art in the potential of buildings and communities to be integrated in smart grids as well as to discuss the still-open research issues in this field.
Elsevier,

Building and Environment, Volume 97, 15 February 2016, Pages 196-202

Heat map of simulated annual heating demand for South Boston using UMI (a) and daily gas and electricity demand profiles for the highlighted building in South Boston (b).
Targets to reduce GHG emissions in cities require significant political willpower. Transportation and industrial activity have varying contributing factors to GHG in cities, while emissions from buildings is always a key contributor. Understanding building emissions is important in achieving SDG 11 and SDG 13. This article reviews both individual building energy models and regional and country-level building stock models as a way of analysing the energy performance of neighbourhoods.
Key strategies to low energy buildings
The behaviour of a building's occupant has a significant impact on the energy consumption of that building. Behaviour patterns of building occupants are uncertain but social scientists have been studying behaviour patterns for decades. Drawing on this research, this paper explores advances and obstacles in modelling occupant behaviour and the impact this can have on measuring energy consumption. Target 11.6 is concerned with reducing the adverse impacts of cities, therefore understanding and being able to predict occupant behaviour will play an important role in achieving this target.

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