scholarly journals “HerdGPS-Preprocessor”—A Tool to Preprocess Herd Animal GPS Data; Applied to Evaluate Contact Structures in Loose-Housing Horses

Animals ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 1932
Author(s):  
Jennifer Salau ◽  
Frederik Hildebrandt ◽  
Irena Czycholl ◽  
Joachim Krieter
Keyword(s):  
Software Tool ◽  
Farm Animals ◽  
Battery Life ◽  
Gps Data ◽  
Network Parameter ◽  
Livestock Farming ◽  
Trade Offs ◽  
The Hours ◽  
Position Data ◽  
Animal Interaction

Sensors delivering information on the position of farm animals have been widely used in precision livestock farming. Global Positioning System (GPS) sensors are already known from applications in military, private and commercial environments, and their application in animal science is increasing. However, as trade-offs between sensor cost, battery life and sensor weight have to be made, GPS based studies scheduling long data collection periods and including a high number of animals, have to deal with problems like high hardware costs and data disruption during recharging of sensors. Furthermore, human–animal interaction due to sensor changing at the end of battery life interferes with the animal behaviour under analysis. The present study thus proposes a setting to deal with these challenges and offers the software tool “HerdGPS-Preprocessor”, because collecting position data from multiple animals nonstop for several weeks produces a high amount of raw data which needs to be sorted, preprocessed and provided in a suitable format per animal and day. The software tool “HerdGPS-Preprocessor” additionally outputs contact lists to enable a straight analysis of animal contacts. The software tool was exemplarily deployed for one month of daily and continuous GPS data of 40 horses in a loose-housing boarding facility in northern Germany. Contact lists were used to generate separate networks for every hour, which are then analysed with regard to the network parameter density, diameter and clique structure. Differences depending on the day and the day time could be observed. More dense networks with more and larger cliques were determined in the hours prior to the opening of additional pasture.

scholarly journals Precision Technologies to Address Dairy Cattle Welfare: Focus on Lameness, Mastitis and Body Condition

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2253
Author(s):  
Severiano R. Silva ◽  
José P. Araujo ◽  
Cristina Guedes ◽  
Flávio Silva ◽  
Mariana Almeida ◽  
...  
Keyword(s):  
Animal Welfare ◽  
Body Condition ◽  
Farm Animals ◽  
Economic Sustainability ◽  
Farm Animal Welfare ◽  
Livestock Farming ◽  
Technological Support ◽  
Technological Tools ◽  
Cow Welfare ◽  
Time Assessment

Specific animal-based indicators that can be used to predict animal welfare have been the core of protocols for assessing the welfare of farm animals, such as those produced by the Welfare Quality project. At the same time, the contribution of technological tools for the accurate and real-time assessment of farm animal welfare is also evident. The solutions based on technological tools fit into the precision livestock farming (PLF) concept, which has improved productivity, economic sustainability, and animal welfare in dairy farms. PLF has been adopted recently; nevertheless, the need for technological support on farms is getting more and more attention and has translated into significant scientific contributions in various fields of the dairy industry, but with an emphasis on the health and welfare of the cows. This review aims to present the recent advances of PLF in dairy cow welfare, particularly in the assessment of lameness, mastitis, and body condition, which are among the most relevant animal-based indications for the welfare of cows. Finally, a discussion is presented on the possibility of integrating the information obtained by PLF into a welfare assessment framework.

scholarly journals Nanotechnology and Reproductive Management of Farm Animals: Challenges and Advances

Animals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1932
Author(s):  
Nesrein M. Hashem ◽  
Antonio Gonzalez-Bulnes
Keyword(s):  
Management Strategies ◽  
Farming Systems ◽  
Biological Molecules ◽  
Farm Animals ◽  
Physiological Status ◽  
Livestock Farming ◽  
Reproductive Management ◽  
Livestock Farming Systems ◽  
Reproductive Disease ◽  
Nutritional Strategies

Reproductive efficiency of farm animals has central consequences on productivity and profitability of livestock farming systems. Optimal reproductive management is based on applying different strategies, including biological, hormonal, nutritional strategies, as well as reproductive disease control. These strategies should not only guarantee sufficient reproductive outcomes but should also comply with practical and ethical aspects. For example, the efficiency of the biological- and hormonal-based reproductive strategies is mainly related to several biological factors and physiological status of animals, and of nutritional strategies, additional factors, such as digestion and absorption, can contribute. In addition, the management of reproductive-related diseases is challenged by the concerns regarding the intensive use of antibiotics and the development of antimicrobial resistant strains. The emergence of nanotechnology applications in livestock farming systems may present innovative and new solutions for overcoming reproductive management challenges. Many drugs (hormones and antibiotics), biological molecules, and nutrients can acquire novel physicochemical properties using nanotechnology; the main ones are improved bioavailability, higher cellular uptake, controlled sustained release, and lower toxicity compared with ordinary forms. In this review, we illustrate advances in the most common reproductive management strategies by applying nanotechnology, considering the current challenges of each strategy.

ADAPTIVE DATA DISSEMINATION IN MOBILE SENSOR NETWORKS

2009 ◽  
Vol 10 (04) ◽  
pp. 435-457
Author(s):  
ATHANASIOS KINALIS ◽  
SOTIRIS NIKOLETSEAS
Keyword(s):  
Sensor Networks ◽  
Data Dissemination ◽  
High Mobility ◽  
Cost Effective ◽  
Sensor Nodes ◽  
Inhibition Mechanism ◽  
Delivery Ratio ◽  
Message Delivery ◽  
Network Parameter ◽  
Trade Offs

Motivated by emerging applications, we consider sensor networks where the sensors themselves (not just the sinks) are mobile. Furthermore, we focus on mobility scenarios characterized by heterogeneous, highly changing mobility roles in the network. To capture these high dynamics of diverse sensory motion we propose a novel network parameter, the mobility level, which, although simple and local, quite accurately takes into account both the spatial and speed characteristics of motion. We then propose adaptive data dissemination protocols that use the mobility level estimation to optimize performance, by basically exploiting high mobility (redundant message ferrying) as a cost-effective replacement of flooding, e.g. the sensors tend to dynamically propagate less data in the presence of high mobility, while nodes of high mobility are favored for moving data around. These dissemination schemes are enhanced by a distance-sensitive probabilistic message flooding inhibition mechanism that further reduces communication cost, especially for fast nodes of high mobility level, and as distance to data destination decreases. Our simulation findings demonstrate significant performance gains of our protocols compared to non-adaptive protocols, i.e. adaptation increases the success rate and reduces latency (even by 15%) while at the same time significantly reducing energy dissipation (in most cases by even 40%). Also, our adaptive schemes achieve significantly higher message delivery ratio and satisfactory energy-latency trade-offs when compared to flooding when sensor nodes have limited message queues.

scholarly journals Implications of Temperate Agroforestry on Sheep and Cattle Productivity, Environmental Impacts and Enterprise Economics. A Systematic Evidence Map

Forests ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1321
Author(s):  
Matthew W. Jordon ◽  
Kathy J. Willis ◽  
William J. Harvey ◽  
Leo Petrokofsky ◽  
Gillian Petrokofsky
Keyword(s):  
Decision Making ◽  
Environmental Impacts ◽  
Evidence Base ◽  
Agroforestry Systems ◽  
Livestock Farming ◽  
Evidence Map ◽  
Trade Offs ◽  
Temperate Agroforestry ◽  
Heat And Cold Stress ◽  
Context Specific

The environmental impacts of ruminant livestock farming need to be mitigated to improve the sustainability of food production. These negative impacts have been compounded by the increased spatial and cultural separation of farming and forestry across multiple temperate landscapes and contexts over recent centuries, and could at least in part be alleviated by re-integration of livestock and trees via agroforestry systems. Such integration also has the potential to benefit the productivity and economics of livestock farming. However, the delivery of hoped-for benefits is highly likely to depend on context, which will necessitate the consideration of local synergies and trade-offs. Evaluating the extensive body of research on the synergies and trade-offs between agroforestry and environmental, productivity and economic indicators would provide a resource to support context-specific decision making by land managers. Here, we present a systematic evidence map of academic and grey literature to address the question “What are the impacts of temperate agroforestry systems on sheep and cattle productivity, environmental impacts and farm economic viability?”. We followed good practice guidance from the Collaboration for Environmental Evidence to find and select relevant studies to create an interactive systematic map. We identified 289 relevant studies from 22 countries across temperate regions of North and South America, Australasia and Europe. Our preliminary synthesis indicates that there is an emerging evidence base to demonstrate that temperate agroforestry can deliver environmental and economic benefits compared with pasture without trees. However, to date measures of livestock productivity (particularly weather-related mortality and heat- and cold-stress) have received insufficient attention in many temperate agroforestry systems. The evidence base assembled through this work provides a freely accessible resource applicable across temperate regions to support context-specific decision making.

scholarly journals Digital Phenotyping in Livestock Farming

2021 ◽  
Author(s):  
Suresh Neethirajan ◽  
Bas Kemp
Keyword(s):  
Farm Animals ◽  
Great Promise ◽  
Affective States ◽  
Livestock Farming ◽  
Non Invasive ◽  
Clinical Biomarkers ◽  
Digital Phenotyping ◽  
Technology Platforms ◽  
Resilience Indicators ◽  
Species Specific

Currently, large volumes of data are being collected on farms using multimodal sensor technol-ogies. These sensors measure the activity, housing conditions, feed intake, and health of farm animals. With traditional methods, the data from farm animals and their environment can be collected intermittently. However, with the advancement of wearable and non-invasive sensing tools, these measurements can be made in real-time for continuous quantitation relating to clinical biomarkers, resilience indicators, and behavioral predictors. The digital phenotyping of humans has drawn enormous attention recently due to its medical significance, but much research is still needed for the digital phenotyping of farm animals. Implications from human studies show great promise for the application of digital phenotyping technology in modern livestock farming, but these technologies must be directly applied to animals to understand their true capacities. Due to species-specific traits, certain technologies required to assess phenotypes need to be tailored ef-ficiently and accurately. Such devices allow for the collection of information that can better inform farmers on aspects of animal welfare and production that need improvement. By explicitly ad-dressing farm animals’ individual physiological and mental (affective states) needs, sensor-based digital phenotyping has the potential to serve as an effective intervention platform. Future re-search is warranted for the design and development of digital phenotyping technology platforms that create shared data standards, metrics, and repositories.

scholarly journals Does Rural Livestock Farmers’ Have Knowledge of Organic Livestock Farming Practices? Lesson from Southeast, Nigeria

2021 ◽  
Author(s):  
Orgu Kenneth Chima ◽  
Chukwu Andy Onyema ◽  
Onubuogu Gilbert Chinedu ◽  
Esiobu Nnaemeka Success
Keyword(s):  
Organic Farming ◽  
Environmental Sustainability ◽  
Production Systems ◽  
Farm Animals ◽  
Livestock Farming ◽  
Livestock Farmers ◽  
Hot Weather ◽  
The Government ◽  
To Come ◽  
Safe Food

At global level, the use of inorganic feeds, veterinary drugs amongst others can significantly increase farm output in various livestock production systems. However, in recent times, quality-conscious consumers are increasingly seeking environmentally safe and chemical-residue free healthy livestock foods which organic production methods are said to ensure. Livestock Organic farming can offer promising opportunities for ensuring safe food, environmental sustainability, high livestock yield and income. Incidentally, empirical evidence on present discourse is still relatively very little. Although, a significant contribution has been made by various scholars, regrettably, these studies did not dwell on organic livestock practices and their knowledge level in South-east, Nigeria. Therefore, this presents a dearth in research and became increasingly pertinent that the study was systematically undertaken. A multistage and purposive random sampling procedure was used in the selection of 504 respondents who are organic livestock farmers. Data collected was analyzed using mean score analysis. Result shows that farmers had knowledge on practices of extensive system of livestock/poultry farming (X̄=3.49); provision of natural air (X̄=3.50); provision of natural water sprinkling during hot weather (X̄=3.50); rearing animal without antibiotics (X̄=3.56); and treating injured animals organically (X̄=3.48) among others. Incidentally, majority of the livestock farmers lacked knowledge of how to induce ovulation for animals without drugs (X̄=1.88). The inducement of ovulation for farm animals is one of the livestock organic methods used in forcing farm animals to come on heat/ovulation for quick multiplication. This method is harmful both for the animal an eventual consumer. Therefore, it is necessary that extension agents who are subject matter specialist (SMS) in livestock organic farming educate farmers on how to induce ovulation to farm animals organically with support from the government and farmers cooperative membership resources as these would significantly reduce harmful drugs injected to animal for quick ovulation and preserve the life span of the animal and consumers of the animal.

scholarly journals Sensor-data Enabled Indicators in the Investigation of Livestock Resilience

2021 ◽  
Author(s):  
Anne Pennings ◽  
Huib van den Heuvel ◽  
Amalia Mejia Pelaez ◽  
Ingrid Van der Werff ◽  
Suresh Neethirajan
Keyword(s):  
Physiological Stress ◽  
Wearable Sensors ◽  
Farming Systems ◽  
Sensor Data ◽  
Farm Animals ◽  
Psychological Resilience ◽  
Affective States ◽  
Livestock Farming ◽  
Complex Concept ◽  
Livestock Farming Systems

Whereas domestication of farm animals has primarily focused on desired productivity traits, the intensification of livestock farming has highlighted the need for improving animal resilience, too. Animal resilience is a complex concept that encompasses the ability for an animal to recover from a particular disturbance. The concept includes resilience to disease, environmental resilience such as extreme and fluctuating climates, but also psychological resilience including stress resilience. Sensor-based data models enable prediction of livestock farming outcomes in response to varying behavioral, physiological, stress and affective states. The quantification of resilience post-disturbance, as well as estimating and predicting resilience pre-disturbance, is challenging. We present a review-based approach in exploring the sensor-data enabled indicators in the investigation of livestock resilience. We assess the intricacies of resilience of farm animals using conceptual, comprehensive, and integrated systems framework. We analyze progress in sensor methods and its possible use to assess various dynamic indicators of livestock resilience. With the rise of sensor-based technologies for livestock farming systems, accurate and sophisticated monitoring systems of animal resilience become more readily available. Wearable sensors, tracking systems, as well as automatic milking systems, provide a way to continuously collect large amounts of quantitative and qualitative data that aid the monitoring of not only health, productivity, and welfare aspects, but also resilience. Sensor-based technologies help breeding goals by contributing to the understanding of the complex, multidimensional framework of livestock resistance. Animal resilience is an essential trait that should be promoted to improve the sustainability of intensive livestock farming. Through digitalization of data collection, farmers can make better livestock management decisions by enhanced understanding of the indicators of environmental, health and psychological resilience, and will be able to predict degrading resilience.

scholarly journals Software and Hardware Requirements and Trade-Offs in Operating Systems for Wearables: A Tool to Improve Devices’ Performance

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1904 ◽  
Author(s):  
Vicente J. P. Amorim ◽  
Mateus C. Silva ◽  
Ricardo A. R. Oliveira
Keyword(s):  
Operating Systems ◽  
Software Tool ◽  
Wearable Devices ◽  
End User ◽  
Performance Impact ◽  
Performance Improvements ◽  
Trade Offs ◽  
Speed Up ◽  
Software And Hardware ◽  
Hard Real Time

Wearable device requirements currently vary from soft to hard real-time constraints. Frequently, hardware improvements are a way to speed-up the global performance of a solution. However, changing some parts or the whole hardware may increase device complexity, raising the costs and leading to development delays of products or research prototypes. This paper focuses on software improvements, presenting a tool designed to create different versions of operating systems (OSs) fitting the specifications of wearable devices projects. Authors have developed a software tool allowing the end-user to craft a new OS in just a few steps. In order to validate the generated OS, an original wearable prototype for mining environments is outlined. Resulting data presented here allows for measuring the actual impact an OS has in different variables of a solution. Finally, the analysis also allows for evaluating the performance impact associated with each hardware part. Results suggest the viability of using the proposed solution when searching for performance improvements on wearables.

scholarly journals A Software Tool for a Stochastic Life Cycle Assessment and Costing of Buildings’ Energy Efficiency Measures

2021 ◽  
Vol 13 (14) ◽  
pp. 7975
Author(s):  
Edoardo Baldoni ◽  
Silvia Coderoni ◽  
Elisa Di Giuseppe ◽  
Marco D’Orazio ◽  
Roberto Esposti ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Life Cycle Assessment ◽  
Life Cycle ◽  
Environmental Performance ◽  
Software Tool ◽  
Investment Projects ◽  
Trade Offs ◽  
Efficiency Measures ◽  
Support Decision Making

This article presents a novel software tool for the assessments of life-cycle environmental impacts and costs, which is aimed to support decision-making in the design phase of retrofit interventions in the building sector. By combining Life Cycle Costing (LCC) and Life Cycle Assessment (LCA) calculations and functionalities, this tool allows evaluating the long-term trade-offs between economic and environmental performance of investment projects in energy efficiency for buildings, while accounting for uncertainties in input parameters and economic scenarios. A major novelty of the software tool is the stochastic nature of both the LCC and LCA dimensions. The LCA is implemented with Monte-Carlo methods, while the LCC accounts for the probabilistic interdependence of macroeconomic variables over time. The software also includes advanced specific tools for parametrization and sensitivity analysis. Exemplary applications are presented in order to illustrate the novelty and the functionalities of the software tool.

Optimising Cloud Operation Cost Utilising External Memory

2020 ◽  
Vol 9 (2) ◽  
pp. 88-106
Author(s):  
Neil Hyland ◽  
Shawn E. O'Keeffe
Keyword(s):  
Cost Savings ◽  
Software Tool ◽  
External Memory ◽  
Analysis Tool ◽  
Cloud Processing ◽  
System A ◽  
Point Cloud Processing ◽  
Trade Offs ◽  
Execution Speed ◽  
Entire Dataset

Handling large volumes of data on computers incur operational costs when physical hardware is considered, especially RAM, creating a need for intelligent solutions that both maintain an acceptable level of performance and enable cheaper scaling. The authors extend their previous work converting their existing point cloud processing and analysis tool to use external memory via the STXXL C++ library, replacing the entire dataset storage layer with STXXL's intelligent caching system. A rationale for adopting this technique, and methodology for testing previous and modified versions of the software is put forth, and the authors investigate the behaviour of their software tool to establish trade-offs. Competing versions of their software are fed sample datasets in E57 and IFC formats; the results of which are captured and analysed. The authors find that while execution speed is lowered, reduced memory consumption contributes to a higher throughput, enabling greater efficiency and real hardware cost savings.

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