IoT technologies for precision agriculture: a survey

M Pyingkodi, K Thenmozhi… - 2022 6th …, 2022 - ieeexplore.ieee.org
Precision agriculture is gaining popularity in both commercial and research and
development applications recent days. Plant management systems are constantly evolving …

Autonomic cloud computing based management and security solutions: State‐of‐the‐art, challenges, and opportunities

N Agrawal - Transactions on Emerging Telecommunications …, 2021 - Wiley Online Library
The advancements and rapid adoption of service oriented architecture, utility computing,
virtualization, etc., have emerged in a new computing paradigm called cloud computing, in …

A proposed framework for autonomic resource management in cloud computing environment

M Mangla, S Deokar, R Akhare, M Gheisari - Autonomic Computing in …, 2021 - Springer
The technological revolution during the past decades has resulted in the explosion of data
leading to an emergence of cloud computing that subsequently led to fog computing. These …

[PDF][PDF] A comprehensive review on machine learning approaches for yield prediction using essential soil nutrients

R Prabavathi, BJ Chelliah - Universal Journal of Agricultural …, 2022 - academia.edu
Agriculture is the backbone of India's economy, as it is the most important factor in the
country's socio-economic development. Because of the rapid expansion in human …

A framework for autonomic computing for in situ imageomics

J Kline, C Stewart, T Berger-Wolf… - … Computing and Self …, 2023 - ieeexplore.ieee.org
In situ imageomics is a new approach to study ecological, biological and evolutionary
systems wherein large image and video data sets are captured in the wild and machine …

Intelligent farm meets edge computing: energy-efficient solar insecticidal lamp management

S Shao, Q Zhang, S Guo, L Sun, X Qiu… - IEEE Systems …, 2022 - ieeexplore.ieee.org
Energy-efficient solar insecticidal lamp (SIL) management is an important way to promote
the full deployment and application of SILs in intelligent farms. To improve processing …

Energy, latency and staleness tradeoffs in ai-driven iot

NTR Babu, C Stewart - Proceedings of the 4th ACM/IEEE Symposium on …, 2019 - dl.acm.org
AI-driven Internet of Things (IoT) use AI inference to characterize data harvested from IoT
sensors. Together, AI inference and IoT support smart buildings, smart cities and …

Programming and deployment of autonomous swarms using multi-agent reinforcement learning

J Boubin, C Burley, P Han, B Li, B Porter… - arXiv preprint arXiv …, 2021 - arxiv.org
Autonomous systems (AS) carry out complex missions by continuously observing the state of
their surroundings and taking actions toward a goal. Swarms of AS working together can …

Prowess: An open testbed for programmable wireless edge systems

J Boubin, A Banerjee, J Yun, H Qi, Y Fang… - … and Experience in …, 2022 - dl.acm.org
Edge computing is a growing paradigm where compute resources are provisioned between
data sources and the cloud to decrease compute latency from data transfer, lower costs …

A reflection on ai model selection for digital agriculture image datasets

S Ockerman, J Wu, C Stewart… - 2nd AAAI Workshop on AI …, 2023 - openreview.net
Cameras, sensors, and autonomous vehicles deployed in agricultural settings are producing
large, complex, and highly multidimensional datasets. Artificial intelligence techniques can …