相关论文: Multimodal AI Systems for Enhanced Laying Hen Welf…
Understanding animal vocalizations through multi-source data fusion is crucial for assessing emotional states and enhancing animal welfare in precision livestock farming. This study aims to decode dairy cow contact calls by employing…
Poultry farming faces increasing pressure to meet productivity targets while ensuring animal welfare and environmental compliance. Yet many small and medium-sized farms lack affordable, integrated tools for continuous monitoring and…
Early-life development strongly influences long-term welfare in laying hens, yet monitoring remains limited by subjective assessment and single-modality tools. This pilot study evaluated the feasibility of a multimodal sensing framework…
Monitoring cattle health and optimizing yield are key challenges faced by dairy farmers due to difficulties in tracking all animals on the farm. This work aims to showcase modern data-driven farming practices based on explainable machine…
Multimodal artificial intelligence (AI) integrates diverse types of data via machine learning to improve understanding, prediction, and decision-making across disciplines such as healthcare, science, and engineering. However, most…
Machine learning (ML) is a rapidly evolving technology with expanding applications across various fields. This paper presents a comprehensive survey of recent ML applications in agriculture for sustainability and efficiency. Existing…
The convergence of IoT sensing, edge computing, and machine learning is transforming precision livestock farming. Yet bioacoustic data streams remain underused because of computational complexity and ecological validity challenges. We…
In the current age, human lifestyle has become more knowledge oriented leading to generation of sedentary employment. This has given rise to a number of health and mental disorders. Mental wellness is one of the most neglected but crucial…
Current AI advances largely rely on scaling neural models and expanding training datasets to achieve generalization and robustness. Despite notable successes, this paradigm incurs significant environmental, economic, and ethical costs,…
This review explores recent advancements in data fusion techniques and Transformer-based remote sensing applications in precision agriculture. Using a systematic, data-driven approach, we analyze research trends from 1994 to 2024,…
Pose estimation serves as a cornerstone of computer vision for understanding animal posture, behavior, and welfare. Yet, agricultural applications remain constrained by the scarcity of large, annotated datasets for livestock, especially…
As global challenges of population growth, climate change, and resource scarcity intensify, the agricultural landscape is at a critical juncture. Sustainable vertical farming emerges as a transformative solution to address these challenges…
The cattle industry has been a major contributor to the economy of many countries, including the US and Canada. The integration of Artificial Intelligence (AI) has revolutionized this sector, mirroring its transformative impact across all…
Additive manufacturing, particularly fused deposition modeling, is transforming modern production by enabling rapid prototyping and complex part fabrication. However, its layer-by-layer process remains vulnerable to faults such as nozzle…
Combining different sensing modalities with multiple positions helps form a unified perception and understanding of complex situations such as human behavior. Hence, human activity recognition (HAR) benefits from combining redundant and…
Pervasive sensing is transforming health and activity monitoring by enabling continuous and automated data collection through advanced sensing modalities. While extensive research has been conducted on human subjects, its application in…
Although multimodal fusion has made significant progress, its advancement is severely hindered by the lack of adequate evaluation benchmarks. Current fusion methods are typically evaluated on a small selection of public datasets, a limited…
With the world population rapidly increasing, transforming our agrifood systems to be more productive, efficient, safe, and sustainable is crucial to mitigate potential food shortages. Recently, artificial intelligence (AI) techniques such…
In this paper, we examine the use of data from multiple sensing modes, i.e., accelerometry and global navigation satellite system (GNSS), for classifying animal behavior. We extract three new features from the GNSS data, namely, distance…
Building multisensory AI systems that learn from multiple sensory inputs such as text, speech, video, real-world sensors, wearable devices, and medical data holds great promise for impact in many scientific areas with practical benefits,…