Challenges to use machine learning in agricultural big data: a systematic literature review

A Cravero, S Pardo, S Sepúlveda, L Muñoz - Agronomy, 2022 - mdpi.com
Agricultural Big Data is a set of technologies that allows responding to the challenges of the
new data era. In conjunction with machine learning, farmers can use data to address …

Machine learning with big data: Challenges and approaches

A L'heureux, K Grolinger, HF Elyamany… - Ieee …, 2017 - ieeexplore.ieee.org
The Big Data revolution promises to transform how we live, work, and think by enabling
process optimization, empowering insight discovery and improving decision making. The …

Age of information: A new concept, metric, and tool

A Kosta, N Pappas, V Angelakis - Foundations and Trends® …, 2017 - nowpublishers.com
Age of information (AoI) was introduced in the early 2010s as a notion to characterize the
freshness of the knowledge a system has about a process observed remotely. AoI was …

[HTML][HTML] Face mask recognition system using CNN model

G Kaur, R Sinha, PK Tiwari, SK Yadav, P Pandey… - Neuroscience …, 2022 - Elsevier
COVID-19 epidemic has swiftly disrupted our day-to-day lives affecting the international
trade and movements. Wearing a face mask to protect one's face has become the new …

Role of IoT technologies in big data management systems: A review and Smart Grid case study

AR Al-Ali, R Gupta, I Zualkernan, SK Das - Pervasive and Mobile …, 2024 - Elsevier
Abstract Empowered by Internet of Things (IoT) and cloud computing platforms, the concept
of smart cities is making a transition from conceptual models to development and …

[HTML][HTML] Real-time big data processing for instantaneous marketing decisions: A problematization approach

A Jabbar, P Akhtar, S Dani - Industrial Marketing Management, 2020 - Elsevier
The collection of big data from different sources such as the internet of things, social media
and search engines has created significant opportunities for business-to-business (B2B) …

kNN-IS: An Iterative Spark-based design of the k-Nearest Neighbors classifier for big data

J Maillo, S Ramírez, I Triguero, F Herrera - Knowledge-Based Systems, 2017 - Elsevier
Abstract The k-Nearest Neighbors classifier is a simple yet effective widely renowned
method in data mining. The actual application of this model in the big data domain is not …

ElStream: An ensemble learning approach for concept drift detection in dynamic social big data stream learning

A Abbasi, AR Javed, C Chakraborty, J Nebhen… - IEEE …, 2021 - ieeexplore.ieee.org
With the rapid increase in communication technologies and smart devices, an enormous
surge in data traffic has been observed. A huge amount of data gets generated every …

Use and adaptations of machine learning in big data—Applications in real cases in agriculture

A Cravero, S Sepúlveda - Electronics, 2021 - mdpi.com
The data generated in modern agricultural operations are provided by diverse elements,
which allow a better understanding of the dynamic conditions of the crop, soil and climate …

A general perspective of Big Data: applications, tools, challenges and trends

L Rodríguez-Mazahua, CA Rodríguez-Enríquez… - The Journal of …, 2016 - Springer
Big Data has become a very popular term. It refers to the enormous amount of structured,
semi-structured and unstructured data that are exponentially generated by high …