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Nowadays, different types of farm management information systems (FMIS) are being used in practice in several sectors of farming, such as dairy, arable, fruits, vegetables, and meat farming. The goal of this research is to identify, evaluate, and synthesize existing FMISs in the Dutch dairy sector and present the state–of–the–art. We performed a mu...
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... comes up with technical reports about the FMISs, and the survey provides information about data used by the FMISs. A summary of the methods per research question is shown in Table 1. ...Citations
... For Tummers et al. (2019), a management system is used to collect, process, store and disseminate information to carry out operations in the business as it provides the data in an informative way to the producer, who is able to make better decisions using the system as it provides better insights that he would not have without its use. Kassahun et al (2022), conducted a survey study of information on the use of management systems used on dairy farms in the Netherlands. The authors combined the use of an online survey questionnaire with literature review and identified the different types of data managed by the different types of systems which included fertility values, cow activity, rumination activity, concentrate feed intake, calving dates, milk production, milk quality attributes (fat percentage, protein percentage, cell count, conductivity), fertilizer use, field location, field area, bull characteristics, feed consumption and cash flow. ...
Family enterprises have as their main characteristic the management by their own family and in them, the family works directly, with or without the help of others. It can be said that family farming represents a social innovation and that, regardless of the size of the enterprise, it must be managed to remain sustainable. With this in mind, this chapter deals with a study that aimed to program a software for the technical and economic management of the dairy production system of family farms, so that their managers will have data for decision-making in the rural business, as well as the professionals of the rural extension can provide rural assistance. The first step of the research was based on the identification and characterization of the evolutionary profile of small family farms, to identifying the technical demands of dairy farming on these family farms. The second step was the development of the computerized app, which used open-source PHP (Hypertext Preprocessor) programming language and was stored on the internet. The application can be accessed at http://www.pmppa.com.br/gestor/, running on the Window platform. The final step was the application test with the researched family farm properties data. The computerized app consists of easy data entry and handling, accessed online, with tools for zootechnical control (nutritional, reproductive and sanitary management) and management (production cost). The result was a free computerized app that generates and provides information in a simple and practical way, providing the family farmer with resources for simple and complex decision making. The application was registered at INPI through the number 512018051699-8.
... These models contribute to understanding the effects of efficiency improvements on animal product availability at the country level [13]. FMISs [14] with milking robots and activity monitors offer distinct advantages in dairy management. ...
The Value Chain Optimizer is a PHP-based web application designed for dairy shop management. Functionalities include category and company management, product handling, search, invoice generation, and report creation. The project aims to streamline dairy shop operations, enhance sales tracking, and facilitate efficient product management. This research paper will delve into the development, implementation, and impact of the Value Chain Optimization in Dairy Product Management, exploring its features, usability, and potential contributions to dairy shop administration. Our system is a game-changer in terms of boosting efficiency and promoting inclusivity among different farming scales and levels of technology. Based on the results, economic costs and environmental impacts decreased by 18.5% and 25%, respectively with user-friendly interfaces and adaptable functionalities, this system remains relevant and valuable in all types of dairy farming environments.
... To date, the market for technological solutions offers a variety of software products that allow dairy cattle breeding, the control of productive indicators and timely identification and notification of the hunting of animals and upcoming calving-these and other software functions are an effective means of making managerial decisions. In addition to software, the level of interest in the means of robotization of technological processes (milking robots and feed distribution robots) has increased from small farms over the past 10 years [4]. ...
Practical experience demonstrates that the development of agriculture is following the path of automating and robotizing operational processes. The operation of feed pushing in the feeding alley is an integral part of the feeding process and significantly impacts dairy cattle productivity. The aim of this research is to develop an algorithm for automatic positioning and a mobile remote-control system for a wheeled robot on a dairy farm. The kinematic and dynamic motion characteristics of the wheeled robot were obtained using software that allows simulation of physical processes in an artificial environment. The mobile application was developed using Swift tools, with the preliminary visualization of interfaces and graphic design. The system uses technical vision based on RGB cameras and programmed color filters and is responsible for the automatic positioning of the feed-pusher robot. This system made it possible to eliminate the inductive sensors from the system and suspend the labor effort required for assembling the contour wire of the feed alley. By assessing the interaction between the mobile app and the feed pusher via the base station connected to the Internet and located on the farm, the efficiency and accuracy of the feedback was measured. Furthermore, remote changes in the operating regime of the robot (start date) were proven to be achievable, and the productiveness of the food supplement dispenser also became manageable.
... Demand for this kind of digital service is high given their direct impact on a herd's animal welfare and health [1], leading to measurable improvements in dairy farms' most relevant income streams (milk and animal sales) [7]. Furthermore, the data basis enabling such digital services is retrievable from a variety of embedded systems (e.g., cow transponders) and cyber-physical systems (e.g., automatic milking systems), whose adoption is on the rise at German dairy barns [3,5,8]. Furthermore, although data transfer among those systems often still requires manual effort from the farmer [8], the functionality of digital herd management and health monitoring services is already very advanced, including the application of artificial intelligence (AI) data analytics [9]. ...
... Furthermore, the data basis enabling such digital services is retrievable from a variety of embedded systems (e.g., cow transponders) and cyber-physical systems (e.g., automatic milking systems), whose adoption is on the rise at German dairy barns [3,5,8]. Furthermore, although data transfer among those systems often still requires manual effort from the farmer [8], the functionality of digital herd management and health monitoring services is already very advanced, including the application of artificial intelligence (AI) data analytics [9]. ...
... By contrast, digital services on ecological sustainability for dairy farmers, comprising Greenhouse Gas (GHG) emission calculators and digital energy management services (DEMS), are not yet even in the scope of most FMIS [6,8]. However, the necessity of having such services is high given their expected contribution to achieving global sustainability goals [10]. ...
The adoption of farm management information systems (FMIS) is on the rise at German dairy farms given their benefits in supporting and automating decision-making processes. However, the offering scope of FMIS for dairy farmers is limited, with digital services mostly focusing on animal-related data and overall economic insights. By contrast, digital energy management services (DEMS) are not yet established as an integral part of FMIS despite their expected positive contribution to a dairy farm's ecological sustainability and profitability. Against this background, the aim of this study was to find out if there is a hitherto undetected market opportunity for FMIS providers offering DEMS to German dairy farmers. To achieve this aim, the as-is market offering was screened looking at seven pre-defined DEMS, and customer preferences were investigated based on online survey responses from 74 German dairy farmers. Results of the survey indicate a high relevance of DEMS, which especially applies for optimization-oriented energy data analyses. The market coverage of such digital services, on the other hand, is not yet adequate. Hence, for providers of FMIS, we see a promising market opportunity to expand their offering by starting to deploy selected DEMS to German dairy farmers.
... CORBA is a development standard published by the Object Management Group (OMG) to support the collaborative nature of application systems, and it is a development technology for management information systems. With the rapid development of information technology such as computer technology and network communication, CIS system has been widely used in the field of school management, which provides a more convenient and accurate way to share information resources, data processing and analysis [3] .The specific interaction between CORBA management components, applied in the management information system, can not only realize the integration of information resources and data, but also free management staff from the heavy and complex data processing work [4] . ...
... Moreover, a wealth of pesticide monitoring/detection methods and techniques has been introduced during the last years for both in field and in laboratory analysis [17][18][19]. Furthermore, the wide exploitation of decision support systems for enhancing agricultural productivity through holistic farm management [20] has led to adoption of precision agriculture management systems by farms of diverse size, ranging from small to big farms [21], with special further expansion in the livestock production sector [22]. ...
... There are many farm management and information systems (FMIS) available on the market. What they virtually all have in common is not mapping an entire farm, although terms such as "digital shadow" or "digital twin" can increasingly be found in the literature (e.g., [170,171]). To date, only so-called isolated solutions can be assumed. ...
The main impetus for the global efforts toward the current digital transformation in almost all areas of our daily lives is due to the great successes of artificial intelligence (AI), and in particular, the workhorse of AI, statistical machine learning (ML). The intelligent analysis, modeling, and management of agricultural and forest ecosystems, and of the use and protection of soils, already play important roles in securing our planet for future generations and will become irreplaceable in the future. Technical solutions must encompass the entire agricultural and forestry value chain. The process of digital transformation is supported by cyber-physical systems enabled by advances in ML, the availability of big data and increasing computing power. For certain tasks, algorithms today achieve performances that exceed human levels. The challenge is to use multimodal information fusion, i.e., to integrate data from different sources (sensor data, images, *omics), and explain to an expert why a certain result was achieved. However, ML models often react to even small changes, and disturbances can have dramatic effects on their results. Therefore, the use of AI in areas that matter to human life (agriculture, forestry, climate, health, etc.) has led to an increased need for trustworthy AI with two main components: explainability and robustness. One step toward making AI more robust is to leverage expert knowledge. For example, a farmer/forester in the loop can often bring in experience and conceptual understanding to the AI pipeline-no AI can do this. Consequently, human-centered AI (HCAI) is a combination of "artificial intelligence" and "natural intelligence" to empower, amplify, and augment human performance, rather than replace people. To achieve practical success of HCAI in agriculture and forestry, this article identifies three important frontier research areas: (1) intelligent information fusion; (2) robotics and embodied intelligence; and (3) augmentation, explanation, and verification for trusted decision support. This goal will also require an agile, human-centered design approach for three generations (G). G1: Enabling easily realizable applications through immediate deployment of existing technology. G2: Medium-term modification of existing technology. G3: Advanced adaptation and evolution beyond state-of-the-art.
