The Potential of AI and ChatGPT in Improving Agricultural Injury and Illness Surveillance Programming and Dissemination.

Generative Artificial Intelligence (AI) provides unprecedented opportunities to improve injury surveillance systems in many ways, including the curation and publication of information related to agricultural injuries and illnesses. This editorial explores the feasibility and implication of ChatGPT integration in an international sentinel agricultural injury surveillance system, AgInjuryNews, highlighting that AI integration may enhance workflows by reducing human and financial resources and increasing outputs. In the coming years, text intensive natural language reports in AgInjuryNews and similar systems could be a rich source for data for ChatGPT or other more customized and fine-tuned LLMs. By harnessing the capabilities of AI and NLP, teams could potentially streamline the process of data analysis, report generation, and public dissemination, ultimately contributing to improved agricultural injury prevention efforts, well beyond any manually driven efforts.

An Argument Against Cross-Platform Development: Lessons From an Augmented Reality App Prototype for Rural Emergency Responders.

BACKGROUND: Mobile augmented reality (MAR) apps offer potential support for emergency responders in rural areas. OBJECTIVE: In this report, we described lessons learned from the development process of augmented reality (AR) Farm Mapping to Assist, Protect and Prepare Emergency Responders (MAPPER), a MAR app that provides emergency responders onsite information about the agricultural operation they enter. METHODS: Cross-platform frameworks were used to create AR MAPPER to accommodate budget constraints and overcome issues with markerless MAR technologies. Although the single codebase and Web technologies streamlined development, cross-device hardware limitations impacted location accuracy, lengthened the development cycle, and required regular updates to third-party libraries. RESULTS: A hybrid development approach of using Web-based technologies with native tie-ins for specialized components and enhanced performance cut time and costs. This also led to consistency across multiple platforms and ensured that there is only a single set of source files to modify for Android and iPhone operating systems. Meanwhile, active development was delayed by some major hurdles. Apple and Google both released new versions of their operating systems, and the Wikitude framework issued four major updates, each of which brought with it some important enhancements and also led to some new issues. CONCLUSIONS: Developers should consider single platform native development to benefit from platform-specific MAR implementations and to avoid development, testing, and maintenance costs associated with cross-platform implementation. Emergency response organizations may be more likely to utilize a single platform across the devices used by their command staff. This also reduces the benefits of cross-platform development. Furthermore, providing map-based, non-AR cross-platform apps for landowners, farmers, and ranchers would help improve and maintain data quality, which is crucial for the utility and user experience of MAR apps.

Augmented Reality Farm MAPPER Development: Lessons Learned from an App Designed to Improve Rural Emergency Response.

Fire departments have right-of-entry to most commercial industrial sites and preemptively map them to identify the onsite resources and hazards they need to promptly and safely respond to an emergency event. This is not the case for private farms. Emergency responders are blind to resources and hazards prior to arrival and must spend critical minutes locating them during an emergency response at a farm location. The original 2013 Farm Mapping to Assist, Protect and Prepare Emergency Responders (Farm MAPPER) project was undertaken to develop a method to give emergency responders an up-to-date view of on-farm hazard information to safely and efficiently conduct emergency response activities on private agricultural operations. In 2017, an augmented reality version of Farm MAPPER was developed to combine the technological advantages of geographic information system-based data points with a heads-up display and graphical overlay of superimposed hazard imagery and informative icons. The development and testing of this iOS- and Android-ready prototype uncovered lessons learned applicable to other mobile-based apps targeting farmers, ranchers, and rural populations faced with limited or inconsistent mobile internet connectivity.