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In the last ten years, the development of automated agricultural machinery has seen noteworthy advancements. Nevertheless, the successful commercialization of these technologies depends critically on their ability to operate safely. This study evaluated the advantages and limitations of current risk assessment and hazard analysis methods currently used to ensure the safety of autonomous agricultural machines. An online survey containing 18 questions was distributed to 711 participants identified as potential individuals who are currently working or have worked on autonomous agricultural machines to determine the type and frequency of risk assessment and hazard analysis methods applied on autonomous agricultural machines, examine the advantages and limitations of each method, and investigate the perceived effectiveness of each method. Frequency analysis was used to determine the most and least utilized risk assessment and hazard analysis methods. The advantages and limitations of each risk assessment and hazard analysis approach were compared. Descriptive statistics (counts, means, medians, percent) and frequency analysis of the variables were used. The three main types of risk assessment and hazard analysis techniques applied to autonomous agricultural machines. The methods are (a) Informal Group Analysis (e.g., Brainstorming), (b) Hazard Analysis and Risk Assessment (HARA), and (c) Failure Mode and Effects Analysis (FMEA). Replicability is perceived as the main advantage of FMEA and HARA, while cost-effectiveness is the main advantage of Informal Group Analysis. The need to have pre-existing data of the autonomous agricultural machine at hand to be able to perform risk assessment and subjectivity are the main limitations of FMEA, HARA, and Informal Group Analysis dealing with novel and revolutionary autonomous agricultural machines. Industry experts do not believe that the risk assessment and hazard analysis procedures now used are reliable and efficient enough to guarantee the safety of autonomous agricultural tractors. This study reveals important information about the current state of risk assessment and hazard analysis methods in the context of autonomous agricultural machinery. This knowledge can inform future research, policy development, and industry practices to ensure the safety of autonomous agricultural machines. [ABSTRACT FROM AUTHOR]

As agriculture becomes an increasingly data-driven sector, it is important to understand the technology use and barriers by the service providers who work closely with producers. This is especially important as these individuals can serve as drivers for technology adoption by farmers and ranchers. Although many surveys have looked at technology adoption by producers, little data on agricultural industry service providers exists. Surveys of Extension Professionals (EP) in Iowa, Michigan, North Dakota, Ohio, and Wisconsin, and several categories of Agricultural Service Providers (ASP) in Wisconsin were administered in 2018 to determine satisfaction with internet service and to learn more about information and technology usage and potential barriers to its adoption within the industry. In addition, follow-up informational telephone interviews were conducted with 13 Wisconsin EP. A paper survey was administered to ASP, which had a response rate of 35% (N=462). A similar online survey was administered to EP having an estimated 23% response rate (N=223). The frequency of transmission of data, information, and recommendations was high but specialized for both groups with more frequent use in crop production versus livestock (including dairy). The most commonly-cited barriers associated with the adoption of digital technologies by ASP were related to attracting and hiring well-qualified IT employees, training for both employees and clients, and data security. While data security was a commonly cited barrier, 16% of ASP worked for companies that did not have written policies on data privacy. ASP and EP consider their clients to be adept at using text messages, images, maps, and smartphones. They do not consider their clients to be skilled in their use of digitally accessed and used financial statements, spreadsheets, or laboratory analysis reports. Additional training should be better focused on these areas for ASP and EP which would allow them to be more effective in educating producers and to better realize the value associated with more thoughtful and widespread digital technology adoption. [ABSTRACT FROM AUTHOR]

Technology continues to advance in agricultural machines and includes the development of highly automated, robotic, autonomous, and other types of machines used in fields, farmsteads, buildings, and other farm production locations. New engineering design and safety-related standards have been developed in the past half-decade, but safety remains a concern of key stakeholders and is a barrier that could influence widespread adoption. A survey of practicing engineers and researchers involved with highly automated and autonomous agricultural machine design will be presented that shows the methods for risk assessment and control currently in use including different frameworks for hazard and failure identification, prediction, and quantification. The use of engineering design standards (ASABE, ISO, and others) among practitioners is discussed including some important needs that go beyond obstacle detection and injury prevention for operators. These include safety and risk issues connected to animals, property, civic infrastructure, downtime, cyber, and environmental risk. Commonly used risk assessment methods such as the related failure modes and effects analysis (FMEA) or hazard analysis and risk assessment (HARA) are a useful starting point but are based on historical data and experience that can be used to estimate the probability and severity levels of undesirable failures or incidents such as injuries. These data do not yet exist as compared to risk assessment data that can be used to assess incident occurrence probability, failure, detectability, or controllability in more traditional machines. Suggestions are presented for further development of standards and practice recommendations including software needs and operational data that might be used by autonomous machines that is informed by what we do know about past farm incidents that could include accidents, injuries, and other unexpected failures. Keywords. Automation, Autonomous agricultural machinery, Engineering design standards, Farm equipment, Risk assessment, Robotics, Safety. [ABSTRACT FROM AUTHOR]

As agriculture becomes an increasingly data-driven sector, it is important to understand the technology use and barriers by the service providers who work closely with producers. This is especially important as these individuals can serve as drivers for technology adoption by farmers and ranchers. Although many surveys have looked at technology adoption by producers, little data on agricultural industry service providers exists. Surveys of Extension Professionals (EP) in Iowa, Michigan, North Dakota, Ohio, and Wisconsin, and several categories of Agricultural Service Providers (ASP) in Wisconsin were administered in 2018 to determine satisfaction with internet service and to learn more about information and technology usage and potential barriers to its adoption within the industry. In addition, follow-up informational telephone interviews were conducted with 13 Wisconsin EP. A paper survey was administered to ASP, which had a response rate of 35% (N=462). A similar online survey was administered to EP having an estimated 23% response rate (N=223). The frequency of transmission of data, information, and recommendations was high but specialized for both groups with more frequent use in crop production versus livestock (including dairy). The most commonly-cited barriers associated with the adoption of digital technologies by ASP were related to attracting and hiring well-qualified IT employees, training for both employees and clients, and data security. While data security was a commonly cited barrier, 16% of ASP worked for companies that did not have written policies on data privacy. ASP and EP consider their clients to be adept at using text messages, images, maps, and smartphones. They do not consider their clients to be skilled in their use of digitally accessed and used financial statements, spreadsheets, or laboratory analysis reports. Additional training should be better focused on these areas for ASP and EP which would allow them to be more effective in educating producers and to better realize the value associated with more thoughtful and widespread digital technology adoption. [ABSTRACT FROM AUTHOR]

Comments that agricultural safety and health professionals in the United States are challenged by how stakeholders assess risk since the 2001 terrorist attacks. Increase of public concern about safety, health and homeland security; Possibility of a major economic crises with an agroterrorist attack; Threat of bioterrorism agents to agriculture.