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The Climate Action and Low Carbon Development Act 2015 provides the statutory basis for the national objective to transition to a low carbon and climate-resilient economy by 2050. Under the Act the Minister for Communications, Climate Action and Environment must make and submit to Government a series of successive National Mitigation Plans and National Adaptation Frameworks. Ireland?s first Statutory National Adaptation Framework (NAF) was published in 2018 and sets out the national strategy to reduce the vulnerability of the country to the negative effects of climate change and to avail of any positive impacts. Twelve key sectors were identified and are required to prepare sectoral adaptation plans. The Department of Agriculture, Food and the Marine is responsible for three of those sectors ? Agriculture, Forest and Seafood. This Plan which covers the agriculture, forest and seafood sectors has been prepared in line with the Sectoral Planning Guidelines for Climate Change Adaptation.

The Internet of Things (IoT) has become a major technological revolution. Evaluating any IoT advancements comprehensively is critical to understand the conditions under which they can be more useful, as well as to assess the robustness and efficiency of IoT systems to validate them before their deployment in real life. Nevertheless, the creation of an appropriate IoT test environment is a difficult, effort-intensive, and expensive task; typically requiring a significant amount of human effort and physical hardware to build it. To tackle this problem, emulation tools to test IoT devices have been proposed. However, there is a lack of systematic approaches for evaluating IoT emulation environments. In this paper, we present a requirements-based framework to enable the systematic evaluation of the suitability of an emulated IoT environment to fulfil the requirements that secure the quality of an adequate test environment for IoT. 4th International Workshop on Requirements Engineering for Self-Adaptive, Collaborative, and Cyber Physical Systems (RESACS 2018), Banff, Canada, 20-24 August 2018 Science Foundation Ireland European Research Council

Under the public notification system in respect of applications for grant aid for afforestation in excess of 2.5 hectares, detailed below are applications received by the Forest Service.

Senior managers of two German mid-sized world market leaders in sensor electronics (ifm electronic) and mechanical engineering (GEA Group) discuss the opportunities and barriers of developing smart service innovations. The case study addresses different roles and patterns in ecosystems of multiple collaborating actors in different stages of development. The open-end discussion invites learners to evaluate the opportunities from different perspectives based on industry-specific experiences.

Worldwide there are millions of bridges and overpasses that need documentation, inspection, and maintenance. Aerial laser scanning has the potential to assist in this process not only through the initial documentation stage but through the automated creation of three-dimensional, computational models and a further integration of that data with the surrounding environment. This paper outlines the difficulties related to effective vertical data capture for major infrastructure elements and recommends specific approaches towards a geometric optimization of this problem. Results of the current level of viability using a test area in Dublin, Ireland are included based on the application of this optimization. IABSE Conference, Rotterdam, The Netherlands, 6-8 May 2013 European Research Council

In many countries with intensive agriculture, water quality is a major issue and phosphorus (P) loss from soils to water is a major pressure. In Ireland, the EU Nitrates Directive Regulations aim to minimise these losses. This study measured the effects of P source management on P transfer across the nutrient transfer continuum from soils to water and subsequent water quality and agronomic impacts in a dairy-dominated, highly stocked and intensively monitored 7.6 km2 grassland catchment with mostly free draining soils over three years. Monitoring included farm P management, surface soil P concentrations, ground- and stream-water concentrations and stream flow. Reduced P source pressure was indicated by: a) lower farm-gate P balances (2.4 kg ha-1 yr-1), higher P use efficiencies (89%) and lower inorganic fertilizer P use (5.2 kg ha-1 yr-1) relative to previous studies, b) almost no P application during the winter to avoid incidental P transfers, and c) decreased proportions of soils with excessive P concentrations (32% to 24%). Over the same period, milk outputs of 14,585 l ha-1 and gross margins of €3,130 ha-1 indicated that production and profitability remained comparable with the top 10% of dairy farmers nationally. Declines in delayed flow and interflow pathway P concentrations during the winter months indicated some response in P delivery in surface water. However, delayed baseflows in the wetter third year resulted in elevated P concentrations and, overall, there were no clear trends in stream biological quality. This suggests that the impact of policy measures may be felt sooner closer to the source end of the nutrient transfer continuum, in soil P concentrations, for example, and a time lag may occur at the other end in P delivery to streams and stream biological quality, with implications for time frames of policy efficacy and policy monitoring. Wageningen Soil Conference 2017, Wageningen, Netherlands, 27-31 August 2017 Does not appear in published book of abstracts - AC University College Dublin

Internet of Things (IoT) systems produce large amounts of raw data in the form of log files. This raw data must then be processed to extract useful information. Machine Learning (ML) has proved to be an efficient technique for such tasks, but there are many different ML algorithms available, each suited to different types of scenarios. In this work, we compare the performance of 22 state-of-the-art supervised ML classification algorithms on different IoT datasets, when applied to the problem of anomaly detection. Our results show that there is no dominant solution, and that for each scenario, several candidate techniques perform similarly. Based on our results and a characterization of our datasets, we propose a recommendation framework which guides practitioners towards the subset of the 22 ML algorithms which is likely to perform best on their data. 2019 IEEE 5th World Forum on Internet of Things (WF-IoT'19)2019 IEEE 5th World Forum on Internet of Things (WF-IoT), Limerick, Ireland, 15-18 April 2019 European Commission - European Regional Development Fund Science Foundation Ireland

Policymakers, farm advisors and water agencies require up-to-date national maps of critical source areas (CSAs) of nitrogen (N) and phosphorus (P) losses from agricultural land to improve catchment management decisions. The DiffuseTools project aimed to achieve this in Ireland by updating the existing Catchment Characterisation Tool and sub-model NCYCLE_IRL, which predicts environmental losses of N and P from the farm via surface runoff, leaching, denitrification and volatilisation. Updates included (i) using improved national maps of farm-scale source loadings as inputs, (ii) sub-field scale modelling of surface transport risk using soil topographic indices derived from 1 m and 5 m NEXTMap digital elevation models (DEMs), (iii) modelling hydrological disconnectivity from microtopography (HSA Index) and reinfiltration (SCIMAP), (iv) improving the national ditch and stream channel network used by the model by DEM extraction, and (v) using SCIMAP to improve predictions of erosion risk. The improved national source loading maps included mean nationally weighted farm-gate N and P imports (fertilizer, feed and livestock) and balance surpluses (kg/ha) calculated for each stocking rate and soil group (land use potential) category within each sector type (dairy, mixed livestock, suckler cattle, non-suckler cattle, sheep and tillage), using annual Teagasc National Farm Survey data (2008-15). Furthermore, updated national maps of soil P and atmospheric N and P deposition inputs were also used within the national source loading maps to improve model performance. National CSA maps for N and P for each pathway were then produced and evaluated using water quality monitoring data and field observations from the Environmental Protection Agency and Teagasc Agricultural Catchments Programme. These maps will be able to support sustainable intensification by informing farm and catchment management decisions such as where to cost effectively target mitigation measures to reduce environmental losses, where to distribute nutrient surpluses (to non-CSAs in nutrient deficit), and improving functional land management. LUWQ 2019: International Interdisciplinary Conference on Land Use and Water Quality. Agriculture and the Environment. Aarhus, Denmark, 3-6 June 2019 Check for published version during checkdate report - AC Environmental Protection Agency

Imagine you are checking in to your hotel for a well-deserved holiday. You are looking forward to a break away from the modern connected world, but are greeted by a robotic dinosaur at the reception desk. Welcome to the Henn-na Hotel in Nagasaki, Japan, the world's first fully manned robotic hotel.