Space and Applications of Artificial Intelligence

Pattnayak, Parthasarathi; Patnaik, Sanghamitra

doi:10.1109/ocit56763.2022.00039

Cited by 1 publication

(1 citation statement)

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“…Machine learning equips spacecraft and rovers, like NASA's Mars rovers, to navigate and collect data independently, optimizing paths in real time. Research expands AI's role in autonomous spacecraft technology and space law [105,106], with a focus on developing trusted AI systems for mission autonomy [107]. These AI advancements promise to significantly enhance the efficiency, autonomy, and intelligence of space missions, marking a new era in space exploration and analysis.…”

Section: Space Exploration: Autonomous Exploration and Data Analysismentioning

confidence: 99%

Artificial Intelligence: A Promising Tool for Application in Phytopathology

González-Rodríguez,

Izquierdo-Bueno,

Cantoral

et al. 2024

Horticulturae

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Artificial intelligence (AI) is revolutionizing approaches in plant disease management and phytopathological research. This review analyzes current applications and future directions of AI in addressing evolving agricultural challenges. Plant diseases annually cause 10–16% yield losses in major crops, prompting urgent innovations. Artificial intelligence (AI) shows an aptitude for automated disease detection and diagnosis utilizing image recognition techniques, with reported accuracies exceeding 95% and surpassing human visual assessment. Forecasting models integrating weather, soil, and crop data enable preemptive interventions by predicting spatial-temporal outbreak risks weeks in advance at 81–95% precision, minimizing pesticide usage. Precision agriculture powered by AI optimizes data-driven, tailored crop protection strategies boosting resilience. Real-time monitoring leveraging AI discerns pre-symptomatic anomalies from plant and environmental data for early alerts. These applications highlight AI’s proficiency in illuminating opaque disease patterns within increasingly complex agricultural data. Machine learning techniques overcome human cognitive constraints by discovering multivariate correlations unnoticed before. AI is poised to transform in-field decision-making around disease prevention and precision management. Overall, AI constitutes a strategic innovation pathway to strengthen ecological plant health management amidst climate change, globalization, and agricultural intensification pressures. With prudent and ethical implementation, AI-enabled tools promise to enable next-generation phytopathology, enhancing crop resilience worldwide.

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Section: Space Exploration: Autonomous Exploration and Data Analysismentioning

confidence: 99%