IoT solutions with artificial intelligence technologies for precision agriculture: Definitions, applications, challenges, and opportunities
EEK Senoo, L Anggraini, JA Kumi, BK Luna… - …, 2024 - search.proquest.com
The global agricultural sector confronts significant obstacles such as population growth,
climate change, and natural disasters, which negatively impact food production and pose a …
climate change, and natural disasters, which negatively impact food production and pose a …
Combining Machine Learning and Edge Computing: Opportunities, Challenges, Platforms, Frameworks, and Use Cases
In recent years, we have been observing the rapid growth and adoption of IoT-based
systems, enhancing multiple areas of our lives. Concurrently, the utilization of machine …
systems, enhancing multiple areas of our lives. Concurrently, the utilization of machine …
Using mobile edge AI to detect and map diseases in citrus orchards
Deep Learning models have presented promising results when applied to Agriculture 4.0.
Among other applications, these models can be used in disease detection and fruit counting …
Among other applications, these models can be used in disease detection and fruit counting …
Wearable technology for smart manufacturing in industry 5.0
The innovation of wearable Internet of Things devices has fuelled the transition from Industry
4.0 to Industry 5.0. Increasing resource efficiency, safety, and economic efficiency are some …
4.0 to Industry 5.0. Increasing resource efficiency, safety, and economic efficiency are some …
Modeling an edge computing arithmetic framework for IoT environments
IoT environments are forecasted to grow exponentially in the coming years thanks to the
recent advances in both edge computing and artificial intelligence. In this paper, a model of …
recent advances in both edge computing and artificial intelligence. In this paper, a model of …
Modeling of a generic edge computing application design
Edge computing applications leverage advances in edge computing along with the latest
trends of convolutional neural networks in order to achieve ultra-low latency, high-speed …
trends of convolutional neural networks in order to achieve ultra-low latency, high-speed …
Application of active acoustic transducers in monitoring and assessment of terrestrial ecosystem health—A review
B Rostami, C Nansen - Methods in Ecology and Evolution, 2022 - Wiley Online Library
Urbanization, agricultural production, natural resource extractions and climate change are
global drivers of terrestrial ecosystem degradation and decline in ecosystem health …
global drivers of terrestrial ecosystem degradation and decline in ecosystem health …
Designing RISC-V Instruction Set Extensions for Artificial Neural Networks: An LLVM Compiler-Driven Perspective
KK Balasubramanian, M Di Salvo, W Rocchia… - IEEE …, 2024 - ieeexplore.ieee.org
The demand for Artificial Intelligence (AI) based solutions is exponentially increasing in all
application fields, including low-power devices on the edge. However, due to their limited …
application fields, including low-power devices on the edge. However, due to their limited …
Bringing deep learning to the fields and forests: Leaf reconstruction and shape estimation
One of the indicators of ecosystem health is leaf health. Among the leading indicators
studied in leaves, herbivory and disease presence are relevant indicators of ecosystem …
studied in leaves, herbivory and disease presence are relevant indicators of ecosystem …
A Systematic Literature Review on the Adoption of Edge Computing for Sustainable Development
Digital technologies have been increasingly applied to support the 17 Sustainable
Development Goals (SDGs), which address global challenges, including poverty, inequality …
Development Goals (SDGs), which address global challenges, including poverty, inequality …