AI-Enabled Spatial Intelligence

The integration of AI-driven technologies into society has led to profound changes across various domains, presenting both opportunities and challenges. AI has redefined communication patterns, breaking down barriers and introducing novel modes of engagement, but concerns about authenticity persist. In the realm of work dynamics, AI's automation capabilities have reshaped industries, leading to job displacement and emphasizing the need for investments in education. Personalization and recommender systems powered by AI offer tailored content but raise concerns about bias and echo chambers. AI's influence on social media blurs virtual and physical identities, necessitating measures to safeguard democratic values. Politically, AI presents opportunities for international cooperation but also challenges related to security and governance. Culturally, AI impacts representation and diversity, highlighting the need for inclusive design practices. Economically, AI-driven automation offers efficiency gains but also raises concerns about job displacement and inequality.

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Harvesting Data the Role of AI in Smart Farming and Precision Agriculture

Mahmood,

Waseem,

Abbas

et al. 2024

Advances in Computational Intelligence and Robotics

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Integrating AI into data-driven agriculture is not a cure-all but a potentially transformative tool. Embracing advanced technologies and driving progress can help ensure a more sustainable and profitable agricultural future, meeting the needs of a growing population. This chapter explores the specific role of AI within smart and precision agriculture. The chapter covers the application of AI in data capture ranging from sensor networks, satellite imagery, drone technology, and weather data integration to monitor crop health, soil conditions, and environmental factors in real-time, enhancing precision agriculture. It examines how various data analysis methods encompassing machine learning algorithms, image recognition & computer vision, and predictive analytics interpret data to provide meaningful insights. The chapter also underpinned various data-driven decision-making scenarios such as targeted irrigation, precision pest & disease control, automated weed control, selective harvesting, livestock monitoring % management, crop rotation planning, and planting date optimization.

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AI-Enabled Spatial Intelligence

Cited by 4 publications

References 78 publications

AI-Assisted GIS Toward GEO-AI: Trends and Innovations Overview

AI-Assisted GIS Toward GEO-AI: Trends and Innovations Overview

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Harvesting Data the Role of AI in Smart Farming and Precision Agriculture

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