•Existing definitions of the Internet of Things (IoT) and allied terms are reviewed.•A robust definition of Industrial Internet of Things (IIoT) is proposed.•An analysis framework for ...characterisation and classification of IIoT devices is provided.•Gaps in the current literature and understanding of IIoT are identified.
Historically, Industrial Automation and Control Systems (IACS) were largely isolated from conventional digital networks such as enterprise ICT environments. Where connectivity was required, a zoned architecture was adopted, with firewalls and/or demilitarized zones used to protect the core control system components. The adoption and deployment of ‘Internet of Things’ (IoT) technologies is leading to architectural changes to IACS, including greater connectivity to industrial systems. This paper reviews what is meant by Industrial IoT (IIoT) and relationships to concepts such as cyber-physical systems and Industry 4.0. The paper develops a definition of IIoT and analyses related partial IoT taxonomies. It develops an analysis framework for IIoT that can be used to enumerate and characterise IIoT devices when studying system architectures and analysing security threats and vulnerabilities. The paper concludes by identifying some gaps in the literature.
The concept of twinning an operational physical system with a functional replica is not new, having been practiced in the space sector for over 50 years. Advances in digitalisation have created ...opportunities to extract data, obtain insights and achieve greater situational awareness of a physical system’s performance. Increasing interest in the concept has led to a proliferation of digital twin definitions, which are used to frame discussions about specific digital twins. Consequentially comparison of the capabilities of specific digital twins is difficult as they are analysed using different definitions. This paper proposes an analysis framework that enables the characteristics of all digital twins to be matched to this framework. Using this framework, a digital twin may be characterised, or two or more digital twins may be compared. By establishing a framework that contains common functional characteristics, we aim to reduce the confusion caused by the plethora of digital twin definitions and their interpretation by suppliers. By focusing only on functionality and not addressing non-functional requirements the analysis allows comparison of different physical and logical instantiations of digital twins.
•Limitations of existing digital twin literature reviews.•Functional architecture of a digital twin.•Systematic approach for comparison of digital twins.•Analysis framework for digital twins.
Intensified agricultural production systems relying on larger field sizes and homogeneous landscapes result in land degradation, biodiversity losses, and impaired ecosystem services, particularly ...regulating services such as water and climate regulation. A multifunctional landscape composition and configuration promises higher ecosystem functionality by balancing ecological and economic provisioning functionality for food, fuel, and fiber. However, to the best of our knowledge, not much is known about the synergies and trade-offs of different landscape compositions and configurations and landscape designs providing ecosystem functionality in economic and ecological dimensions.
We addressed the question whether the ecosystem functionality of agricultural landscapes can be improved at given levels of economic valuation. We quantified potential improvements of ecosystem functionality through multifunctional landscape composition and configuration. We identified agricultural landscapes that provide high ecosystem functionality at their level of economic valuation, given that such regions may serve as role models for a target landscape composition.
Using an eco-efficiency approach based on the non-parametric order-m estimator, we quantified potential improvements of ecosystem functionality at the agricultural landscapes scale. We used the 20 km2 hexagonal grid level in the Federal State of North Rhine-Westphalia, Germany. We described landscape composition and configuration using spatially explicit land cover data from the Integrated Administration and Control System (IACS); land value data indicated the economic output of the landscape. We investigated robustness of our results under different grid specifications (10–50 km2) and using subsamples of regions with similar environmental conditions.
We found on average high eco-efficiency of agricultural landscapes in the study region. We also found notable improvement potentials in at least one ecological indicator that were spatially clustered. The results suggest the potential for Pareto improvements, i.e., increasing landscape eco-efficiency without sacrificing economic outputs.
We present a novel empirical approach to evaluate the eco-efficiency of agricultural landscapes and investigate spatial patterns of eco-efficiency at the landscape scale. We modeled landscapes' potential multifunctionality at a fine regional scale using indicators for landscape composition and configuration based on spatially explicit and highly granular land use and land management data. We relied on publicly available data, and our approach can serve to develop monitoring or policy evaluation at the landscape scale.
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•Multifunctional landscape composition and configuration promises higher ecosystem functionality.•We quantify improvement potentials of ecosystem functionality for a given level of economic output.•Eco-efficiency analysis uses granular spatially explicit data to represent economic output and ecosystem functionality.•Agricultural landscapes show spatially clustered improvement potentials in at least one ecological dimension.•Approach can serve to develop and monitor locally adapted policies at landscape scale.
Agricultural systems in Central Europe were redesigned during the last century to attain maximum yields. The results often lead to homogeneous landscapes with only few structures of ecological value ...and have concurrently exacerbated habitat fragmentation. Perennial wildflower strips have become a significant agri-environmental measure (AEM) to counteract the ecological consequences for wild bees and other pollinators in agricultural landscapes. The effectiveness of AEMs depends on the landscape context, but information about geodata sources and spatial scales relevant for the analysis of landscape effects on wild bees is lacking. This study uses data from various sources on land cover and agricultural practices to assess their applicability in an evaluation of perennial wildflower strips as AEM for wild bees in Saxony-Anhalt, Germany. We investigated the relationships of wild bee species diversity and abundance to the landscape context at spatial scales from 200 m to 10 km considering several factors: land cover/land use, protected areas, crop types, agri-environment schemes/greening, intensity of agriculture, and intensity of grassland farming. In general, our results revealed that landscape effects were more relevant for solitary than social wild bees on flower strips, pointing to a higher limitation of solitary wild bees in nesting resources as compared to social wild bees. Numbers of wild bee species and individuals benefitted from bare soil and ecological focus areas in the surroundings up to 3 km distance, whereas the share of Red List solitary bee species was positively influenced by a variety of factors (e.g., wood structures and grasslands) especially at large scales up to 10 km. The comparison of models based on different land cover data sources showed that the lack of geodata resolution can mask landscape effects on wild bees. Altogether, our results suggest a high potential of data from the Basic Digital Landscape Model (DLM), together with the Integrated Administration and Control System (IACS), to indicate effects of landscape structures and agricultural practices on the species composition and distribution of wild bee assemblages in Germany.
•Landscape context affects wild bees on flower strips at multiple spatial scales.•Bare soil and ecological focus areas promote high species diversity and abundance.•Red List bee species benefit from wood structures and grassland in > 3 km distance.•Data on land cover and agricultural practices are key to analyse wild bee habitats.•Multi-scale spatial analyses are essential to evaluate the effectiveness of AEMs.
The next-generation of Industrial Automation and Control Systems (IACS) and Supervisory Control and Data Acquisition (SCADA) systems pose numerous challenges in terms of cybersecurity monitoring. We ...have been witnessing the convergence of OT/IT networks, combined with massively distributed metering and control scenarios such as smart grids. Larger and geographically widespread attack surfaces, and inherently more data to analyse, will become the norm.
Despite several advances in recent years, domain-specific security tools have been facing the challenges of trying to catch up with all the existing security flaws from the past, while also accounting for the specific needs of the next-generation of IACS. Moreover, the aggregation of multiple techniques and sources of information into a comprehensive approach has not been explored in depth. Such a holistic perspective is paramount since it enables a global and enhanced analysis enabled by the usage, combination and aggregation of the outputs from multiple sources and techniques.
This paper starts by providing a review of the more recent anomaly detection techniques for SCADA systems, focused on both theoretical machine learning approaches and complete frameworks. Afterwards, it proposes a complete framework for an Intrusion and Anomaly Detection System (IADS) composed of specific detection probes, an event processing layer and a core anomaly detection component, amongst others. Finally, the paper presents an evaluation of the framework within a large-scale hybrid testbed, and a comparison of different anomaly detection scenarios based on various machine learning techniques.
•Review of the more recent anomaly detection techniques for SCADA system.•A next-generation Intrusion and Anomaly Detection System for IACS.•An extensive evaluation with a large-scale testbed and various ML techniques.
Industrial inputs have replaced crop rotations for fertility and pest management in input-intensive agriculture, resulting in a high number of crop sequence permutations and negative impacts on ...ecosystems and human health. Strengthening diversified and agronomically optimised crop sequences is critical to promoting sustainable practices. Comprehensive crop sequence diagnosis methods play an important role in evaluating and improving current crop sequence practices. However, recent literature has focused on annual crops, leading to biased results in crop sequence analysis for organic farming and livestock regions, where multiannual temporary fodder crops are a key aspect of crop sequences. This paper extends two methods of crop sequence analysis by including multiannual temporary fodder crops. By applying these generalised methods to a case study in the beef grassland regions of Belgium, using IACS crop data from 2015 to 2020, we reveal significant differences in the agronomic quality of the crop sequences across the territory and between organic and non-organic fields. In contrast to the existing literature, the inclusion of multiannual temporary fodder crops highlights the prevalence of high diversity and high agronomic quality sequences in livestock farming regions. Maize monoculture (of low agronomic quality), temporary grasslands (associated with high quality crop sequences) and organic certification are the main drivers of crop sequence quality in the regions studied.
•We used IACS crop data to assess crop sequences in grassland regions.•Farmers do not follow cyclic crop rotations.•Grassland regions show a high share of crop sequences of high agronomic quality.•Multiannual temporary crops play a key role in crop sequence agronomic quality.•Crop sequences certified organic have higher diversity and agronomic quality.
Crop cultivation intensifies globally, which can jeopardize biodiversity and the resilience of cropping systems. We investigate changes in crop rotations as one intensification metric for half of the ...croplands in Germany with annual field-level land-use data from 2005 to 2018. We proxy crop rotations with crop sequences and compare how these sequences changed among three seven-year periods. The results reveal an overall high diversity of crop sequences in Germany. Half of the cropland has crop sequences with four or more crops within a seven-year period, while continuous cultivation of the same crop is present on only 2% of the cropland. Larger farms tend to have more diverse crop sequences and organic farms have lower shares of cereal crops. In three federal states, crop rotations became less structurally diverse over time, i.e. the number of crops and the number of changes between crops decreased. In one state, structural diversity increased and the proportion of monocropping decreased. The functional diversity of the crop sequences, which measures the share of winter and spring crops as well as the share of leaf and cereal crops per sequence, remained largely stable. Trends towards cereal- or leaf-crop dominated sequences varied between the states, and no clear overall dynamic could be observed. However, the share of winter crops per sequence decreased in all four federal states. Quantifying the dynamics of crop sequences at the field level is an important metric of land-use intensity and can reveal the patterns of land-use intensification.
•Spatiotemporal variability of C value for various crop rotations was assessed.•Rotation involving sugar beet and maize increased C value.•Rotation including winter rape could reduce the risk of soil ...erosion.•Monoculture maize could elevate erosion risk by 72 % compared to winter rape.•The results can be useful for spatiotemporally explicit agroecosystem modelling.
In arable land management, different crop rotation patterns and sequences, such as changing agricultural land use to erosion prone crops, or crops providing less ground cover, can greatly influence soil loss rate through their impact on soil cover status (C factor value). The influence of crop rotation on C value and on erosion rate is often determined on an experimental plot scale, so the results are often erroneous when extrapolated to large heterogeneous landscapes, where they fail to capture the spatiotemporal variability beyond the experimental sites. In the present study we have endeavored to investigate the impact of various crop rotation patterns on C value and on subsequent soil erosion rate, at a landscape level, by combining 28 time-series satellite images (from 2013 to 2016) along with annually updated land-use data, via the integrated administration and control system (IACS), from the Uckermark district of north eastern Germany. In total, 21 different crop sequences were investigated. Winter wheat (WW), winter rape (WR), and maize (Mz) were found to be the predominant arable crops grown in the study area. The highest average annual C values were estimated from crop sequences involving Mz and sugar beet (SB), both as pre-crops and succeeding crops. The highest value of 0.39 was computed from SB/Mz rotation. On the other hand, crop rotation involving WR gave significantly lower annual C values in all the years considered, with the lowest average annual C value of 0.07 calculated on WR parcels preceded by winter cereals. It was also apparent that crop rotation patterns influenced C value in a temporally variable manner. Among the self-sequencing patterns, WR/WR reduced the C value significantly compared with Mz/Mz and to a lesser extent compared with WW/WW. Continuous cultivation of Mz increased the potential soil loss rate by as much as 72 % compared to WR/WR and by 51 % compared to WW/WW. It was also possible to determine the spatial distribution of the impact of crop rotation on soil erosion risk within the study area. The results obtained agreed with the results of other international and regional studies. Overall, the output from this research could contribute towards further efficient investigation of the impact of agronomic practices on the environment in a large agricultural landscape, without the need to set up multi-location experimental plots.
To investigative the diagnostic performance of the morphological model, radiomics model, and combined model in differentiating invasive adenocarcinomas (IACs) from minimally invasive adenocarcinomas ...(MIAs).
This study retrospectively involved 307 patients who underwent chest computed tomography (CT) examination and presented as subsolid pulmonary nodules whose pathological findings were MIAs or IACs from January 2010 to May 2018. These patients were randomly assigned to training and validation groups in a ratio of 4:1 for 10 times. Eighteen categories of morphological features of pulmonary nodules including internal and surrounding structure were labeled. The following radiomics features are extracted: first-order features, shape-based features, gray-level co-occurrence matrix (GLCM) features, gray-level size zone matrix (GLSZM) features, gray-level run length matrix (GLRLM) features, and gray-level dependence matrix (GLDM) features. The chi-square test and F1 test selected morphology features, and LASSO selected radiomics features. Logistic regression was used to establish models. Receiver operating characteristic (ROC) curves evaluated the effectiveness, and Delong analysis compared ROC statistic difference among three models.
In validation cohorts, areas under the curve (AUC) of the morphological model, radiomics model, and combined model of distinguishing MIAs from IACs were 0.88, 0.87, and 0.89; the sensitivity (SE) was 0.68, 0.81, and 0.83; and the specificity (SP) was 0.93, 0.79, and 0.87. There was no statistically significant difference in AUC between three models (p > 0.05).
The morphological model, radiomics model, and combined model all have a high efficiency in the differentiation between MIAs and IACs and have potential to provide non-invasive assistant information for clinical decision-making.
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