Review
Agronomy
Ania Cravero, Sebastian Pardo, Samuel Sepulveda, Lilia Munoz
Summary: Agricultural Big Data combined with machine learning can address various challenges in agriculture, such as decision making, water management, soil management, crop management, and livestock management. This study provides a synthesis of the challenges involved in implementing machine learning in agricultural Big Data, along with the techniques and technologies used.
Review
Green & Sustainable Science & Technology
Ania Cravero, Ana Bustamante, Marlene Negrier, Patricio Galeas
Summary: Climate change poses a significant challenge to the sustainability of agriculture. Agricultural Big Data offers valuable tools to address these challenges, but the lack of standards and reference architectures hinders its proper development in the context of climate change.
Article
Computer Science, Information Systems
Laraib Aslam Haafza, Mazhar Javed Awan, Adnan Abid, Awais Yasin, Haitham Nobanee, Muhammad Shoaib Farooq
Summary: The paper discusses the study on the application of big data during the COVID-19 pandemic, conducts a systematic review of relevant literature, and highlights the technological advancements in the field. The research findings successfully address the nature of the COVID-19 crisis, providing a reference for the research community to further address the pandemic.
Review
Automation & Control Systems
Sohail Imran, Tariq Mahmood, Ahsan Morshed, Timos Sellis
Summary: The emergence of healthcare information management systems has generated a vast amount of healthcare data globally. Big data analytics in healthcare offers great potential for improving diagnosis, treatment, and efficiency of healthcare services. Implementing big data analytics in healthcare presents challenges but also opportunities for significant advancements in patient care.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2021)
Review
Green & Sustainable Science & Technology
Mohammad Amiri-Zarandi, Rozita A. Dara, Emily Duncan, Evan D. G. Fraser
Summary: Smart farming utilizes modern technologies and smart devices to improve agriculture, collecting and analyzing data to provide valuable insights. However, the widespread use of data also raises concerns about farmers' privacy. This paper provides a comprehensive review of big data privacy challenges in smart farming and offers existing solutions and advanced technologies.
Review
Computer Science, Artificial Intelligence
Eduardo Tieppo, Roger Robson dos Santos, Jean Paul Barddal, Julio Cesar Nievola
Summary: Research on hierarchical classification and streaming data currently lacks intersection, with studies focusing separately on each area. This study analyzed the characteristics of state-of-the-art works in hierarchical classification for streaming data, identifying problems, datasets, algorithms, evaluation metrics, and research gaps in the field. Results show a need for future research to consider common characteristics shared between hierarchical classification and data stream classification.
ARTIFICIAL INTELLIGENCE REVIEW
(2022)
Review
Computer Science, Information Systems
Rayner Alfred, Joe Henry Obit, Christie Pei-Yee Chin, Haviluddin Haviluddin, Yuto Lim
Summary: This paper explores the applications of Big Data, Machine Learning, and Internet of Things in smart agriculture, focusing on rice production. The study shows that these emerging technologies provide new predictive and identification capabilities for smart rice farming, transforming traditional rice cultivation practices into precision agriculture.
Article
Chemistry, Analytical
Theodoros Alexakis, Nikolaos Peppes, Konstantinos Demestichas, Evgenia Adamopoulou
Summary: The increasing needs for data acquisition, storage and analysis in transportation systems have led to the adoption of new technologies and methods, such as big data techniques and analytics tools. This study aims to provide a distributed architecture platform that addresses the deficiencies in data gathering, storage, and analysis for intelligent transportation systems (ITS). The proposed system utilizes big data frameworks and tools as well as analytics tools to offer continuous collection, storage, and data analysis capabilities, providing a comprehensive solution for ITS applications.
Review
Engineering, Electrical & Electronic
Ulkar Ahmadova, Mustafa Mustafayev, Behnam Kiani Kalejahi, Saeed Saeedvand, Amir Masoud Rahmani
Summary: The Internet of Things (IoT) is a system of physical objects embedded with various sensors that receive information, software, chips, and other technologies to connect and transfer data to other devices through the Internet. With the increasing number of smart devices, big data techniques have been applied in IoT to manage the large amount of information. Through systematic literature review, this paper investigates the latest research methods on big data in IoT approaches published between 2016 and August 2021, analyzing the advantages, drawbacks, and potential research challenges in implementing big data in IoT.
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
(2021)
Review
Computer Science, Information Systems
Pouya Ataei, Alan Litchfield
Summary: This paper conducts a systematic literature review on Big Data Reference Architectures (RA) to facilitate the development and architecture of Big Data systems. The findings suggest that RAs can be an effective tool to tackle complex Big Data system development.
Review
Computer Science, Information Systems
Asadullah Safi, Satwinder Singh
Summary: This study presents a systematic literature survey on various phishing detection approaches, including Lists Based, Visual Similarity, Heuristic, Machine Learning, and Deep Learning based techniques. The research reveals that Machine Learning techniques, particularly the Random Forest Classifier algorithm, are widely used in phishing detection. Furthermore, the Convolution Neural Network (CNN) achieves the highest accuracy of 99.98% in detecting phishing websites according to different studies.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2023)
Review
Computer Science, Information Systems
Ersin Elbasi, Nour Mostafa, Zakwan AlArnaout, Aymen I. Zreikat, Elda Cina, Greeshma Varghese, Ahmed Shdefat, Ahmet E. Topcu, Wiem Abdelbaki, Shinu Mathew, Chamseddine Zaki
Summary: Due to population growth, increasing food demand, changing weather conditions, and water availability, AI has changed the agricultural sector both quantitatively and qualitatively. Smart farming utilizing new IoT technologies and AI has improved seed development, crop protection, and fertilizer usage, benefiting farmers' profitability and the economy. AI is emerging in soil and crop monitoring, predictive analytics, and agricultural robotics. This article surveys AI applications in agriculture, including machine learning, IoT, expert systems, image processing, and computer vision, and explores their benefits and challenges in maintaining quality, productivity, and sustainability in farming.
Review
Green & Sustainable Science & Technology
Ania Cravero, Sebastian Pardo, Patricio Galeas, Julio Lopez Fenner, Monica Caniupan
Summary: Sustainable agriculture is facing challenges due to climate change, and Machine Learning and Agricultural Big Data analysis can provide insights into agricultural production. However, understanding and handling different types of data is necessary for agricultural scientists.
Review
Biology
Daniel Kirk, Cagatay Catal, Bedir Tekinerdogan
Summary: Precision Nutrition research aims to provide more suitable nutritional advice using personal information, and the application of machine learning can aid in developing predictive models. Studies show that machine learning can be used across various domains of nutrition and health to address different problems, with tasks such as classification and recommendation being common.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Review
Environmental Sciences
Jiao Chen, Funing Zhong, Dingqiang Sun
Summary: Farmers' adaptive strategies to climate change are crucial for food security and sustainable environment development. However, a comprehensive evaluation of farmers' adaptations and their potential impacts on climate change is lacking. This study conducted a systematic literature review on farmers' adaptation strategies in China and found that crop variety management, rescheduling farming, increasing production inputs, increasing irrigation, and crop structure management were frequently reported strategies. However, sustainable adaptations such as improving farmland's ecological environment and agronomic water-saving irrigation received less attention. Farmers in northern China were more actively adapting to climate change compared to their counterparts in southern China. Moreover, some high adoption ratio adaptations, like increased chemical inputs, might contribute to increased greenhouse gas emissions and accelerated climate change.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Computer Science, Software Engineering
Ricardo Gacitua, Samuel Sepulveda, Raul Mazo
JOURNAL OF SYSTEMS AND SOFTWARE
(2019)
Review
Forestry
Felipe Vasquez, Ania Cravero, Manuel Castro, Patricio Acevedo
Summary: Wildfires pose significant environmental and economic challenges, necessitating the selection of appropriate technologies and decision support systems. Research shows that using different types of DSS can solve problems related to wildfire detection, prediction, prevention, and monitoring, but there are still many challenges to be addressed in real-world applications.
Article
Education, Scientific Disciplines
Felipe Vasquez-Morales, Ania Cravero-Leal
Summary: This study aims to propose a Big Data architecture for fire management by processing satellite image data to support decision-making. Through practical testing and data analysis, the results show that the resulting images are of significant value for the management of controlled burns within the region.
REVISTA CIENTIFICA
(2021)
Article
Chemistry, Multidisciplinary
Samuel Sepulveda, Ania Cravero
Summary: Most algorithms are used in the domain stage, with transformations being the most common technology. Proposed algorithms mainly stem from academia. The FODA model remains the most frequently used representation for feature modeling, and the majority of papers include empirical validation processes.
APPLIED SCIENCES-BASEL
(2022)
Review
Agronomy
Ania Cravero, Sebastian Pardo, Samuel Sepulveda, Lilia Munoz
Summary: Agricultural Big Data combined with machine learning can address various challenges in agriculture, such as decision making, water management, soil management, crop management, and livestock management. This study provides a synthesis of the challenges involved in implementing machine learning in agricultural Big Data, along with the techniques and technologies used.
Review
Green & Sustainable Science & Technology
Ania Cravero, Ana Bustamante, Marlene Negrier, Patricio Galeas
Summary: Climate change poses a significant challenge to the sustainability of agriculture. Agricultural Big Data offers valuable tools to address these challenges, but the lack of standards and reference architectures hinders its proper development in the context of climate change.
Article
Chemistry, Multidisciplinary
Oscar Aguayo, Samuel Sepulveda
Summary: This paper reviews and synthesizes the research on variability management in dynamic software product lines (DSPLs), focusing on the usage of open-dynamic and closed-dynamic variability, the methodologies employed, and the challenges faced. The primary approach for managing variability in DSPLs is open-dynamic variability, with the MAPE-K control loop being the main methodology. However, further review is needed for response to Research Question 3.
APPLIED SCIENCES-BASEL
(2022)
Review
Green & Sustainable Science & Technology
Ania Cravero, Sebastian Pardo, Patricio Galeas, Julio Lopez Fenner, Monica Caniupan
Summary: Sustainable agriculture is facing challenges due to climate change, and Machine Learning and Agricultural Big Data analysis can provide insights into agricultural production. However, understanding and handling different types of data is necessary for agricultural scientists.
Proceedings Paper
Computer Science, Theory & Methods
Ricardo Gacitua, Mauricio Dieguez, Jaime Diaz, Samuel Sepulveda
2019 38TH INTERNATIONAL CONFERENCE OF THE CHILEAN COMPUTER SCIENCE SOCIETY (SCCC)
(2019)
Proceedings Paper
Computer Science, Theory & Methods
Samuel Sepulveda, Mauricio Dieguez
2019 38TH INTERNATIONAL CONFERENCE OF THE CHILEAN COMPUTER SCIENCE SOCIETY (SCCC)
(2019)
Article
Computer Science, Information Systems
Ania Cravero, Samuel Sepulveda
IEEE LATIN AMERICA TRANSACTIONS
(2019)