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Ivan Sanz-Prieto

Bio: Ivan Sanz-Prieto is an academic researcher from Universidad Internacional de La Rioja. The author has contributed to research in topics: Supply chain & Human behavior. The author has an hindex of 2, co-authored 4 publications receiving 6 citations.

Papers
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Journal ArticleDOI
TL;DR: In this paper, artificial intelligence assisted intelligent planning framework has been proposed to manage the environmental restoration of the terrestrial ecosystem, which helps to protect the natural world and enhances sustainable land resource development.

9 citations

Journal ArticleDOI
TL;DR: A real-time detection framework is proposed for analysing the level of stress for a particular sports person using a hybrid classification technique named Multi-Output Regression with Deep Convolutional Neural Networks to analyse and identify various stress levels and its relationship with data of HRV.

8 citations

Journal ArticleDOI
TL;DR: The results showed the need to identify technological risks; commercial risks regarding the scalability of the business; and financial, legal, fiscal and environmental risks as part of a comprehensive and integral procedure.
Abstract: The dynamics of transformations that the world is experiencing at global dimensions due to the intensity of technological changes demand sophisticated management tools to assess risks in the business and industrial sectors, aimed at ensuring investment security. The objective of this article is to analyze and propose the technical Due Diligence as a methodology to assess risks in Start-up ecosystems. The method used was mixed; a quantitative approach, and the qualitative approach, supported by a literature review with bibliographic arches. The sample was composed of thirty (30) experts, to whom a survey was applied, and to (10) of them, an interview that was subjected to a process of triangulation of the information, which was supported by documentary arches. The results showed the need to identify technological risks (product, service and process); commercial risks regarding the scalability of the business; and financial, legal, fiscal and environmental risks as part of a comprehensive and integral procedure. The objective of this study is to provide a methodology capable of providing numerical data that gives more visibility on the risk of an acquisition in a start-up environment. This methodology is nothing more than a sum of methodologies that are grouped into a single framework, including the different areas of the company (technological, business and financial).

2 citations

Journal ArticleDOI
TL;DR: In this article, the authors proposed a method for recognizing human behavior and considered the challenge of achieving a descriptive marking of activities by labeling individual sub-activities, which can vary from basic behaviors to complicated behaviors.
Abstract: Human activity recognition is one of today's key fields of automated video surveillance. The technology of smart surveillance technology plays a crucial role. Despite efforts in recent years, it is still difficult to recognize human behaviors from live video. Human activity can vary from basic behaviors to complicated behaviors. Depth cameras currently released have an efficient 3D estimate of body connecting locations in the temporal depth map collection. This article proposed a method for recognizing human behavior and considered the challenge of achieving a descriptive marking of activities by labeling individual sub-activities. The behaviors take place over a long period and have many sequential sub-activities. A sports activity prediction of video surveillance framework is proposed in this article. The suggested operation descriptor considers the sequence classification challenge to be the behavior recognition problem. Deep Learning is used to detect human behaviors in the proposed method. The method is tested on two regular identification benchmark functions. Effects of the research revealed that the solution developed exceeds cutting-edge methodologies.

1 citations


Cited by
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Journal ArticleDOI
TL;DR: This work presents a new model to detect in real time the clouds which potentially obstruct the sunrays directed to a specific geographic target, and a novel procedure for the forecasting of the clearness sky index on the target in the fifteen minutes is proposed.

24 citations

Journal ArticleDOI
TL;DR: A recent review of current and future healthcare applications, security, market trends, and IoMT-based technology implementation is presented in this paper , where the potential obstacles and issues of the IoMT system are also discussed.
Abstract: Abstract Extensive research has been conducted on healthcare technology and service advancements during the last decade. The Internet of Medical Things (IoMT) has demonstrated the ability to connect various medical apparatus, sensors, and healthcare specialists to ensure the best medical treatment in a distant location. Patient safety has improved, healthcare prices have decreased dramatically, healthcare services have become more approachable, and the operational efficiency of the healthcare industry has increased. This research paper offers a recent review of current and future healthcare applications, security, market trends, and IoMT-based technology implementation. This research paper analyses the advancement of IoMT implementation in addressing various healthcare concerns from the perspectives of enabling technologies, healthcare applications, and services. The potential obstacles and issues of the IoMT system are also discussed. Finally, the survey includes a comprehensive overview of different disciplines of IoMT to empower future researchers who are eager to work on and make advances in the field to obtain a better understanding of the domain.

20 citations

Journal ArticleDOI
TL;DR: An English teaching reform model based on artificial intelligence algorithms based on the FISST multi-target tracking method, which firstly models the target state and measurement as RFS, and then uses the Bayesian filtering method to recursively calculate the target posterior PDF.
Abstract: In the context of information education, English teaching needs to match the development of artificial intelligence to improve the intelligence of English teaching. Based on the artificial intelligence matching model, this paper constructs an English teaching reform model based on artificial intelligence algorithms. Moreover, based on the FISST multi-target tracking method, this paper firstly models the target state and measurement as RFS, and then uses the Bayesian filtering method to recursively calculate the target posterior PDF, which can estimate the number and state of targets in real time and make up for the shortcomings of traditional tracking methods. In addition, the system proposed in this article can be applied to online English teaching. Through this system, teachers can realize one-to-one matching of students, identify the status of students in time, and give corresponding English teaching methods to different students. Finally, this paper designs a controlled experiment to analyze the performance of the algorithm proposed in this paper. The research results show that the model constructed in this paper has certain practical effects.

13 citations

Journal ArticleDOI
TL;DR: In this paper , the authors have looked at scientific studies that have addressed these challenges with advanced signal processing and Artificial Intelligence (AI) methods and found that HRV signals are both nonstationary and nonlinear and, to the human eye, they appear noise-like.

13 citations

Journal ArticleDOI
08 Nov 2021-Land
TL;DR: In this paper, the authors assess the possibilities of the use of urban big data analytics based on AI-related tools to support the design and planning of cities and introduce a conceptual framework to assess the influence of the emergence of these tools on the design of the cities in the context of urban change.
Abstract: Wide access to large volumes of urban big data and artificial intelligence (AI)-based tools allow performing new analyses that were previously impossible due to the lack of data or their high aggregation. This paper aims to assess the possibilities of the use of urban big data analytics based on AI-related tools to support the design and planning of cities. To this end, the author introduces a conceptual framework to assess the influence of the emergence of these tools on the design and planning of the cities in the context of urban change. In this paper, the implications of the application of artificial-intelligence-based tools and geo-localised big data, both in solving specific research problems in the field of urban planning and design as well as on planning practice, are discussed. The paper is concluded with both cognitive conclusions and recommendations for planning practice. It is directed towards urban planners interested in the emerging urban big data analytics based on AI-related tools and towards urban theorists working on new methods of describing urban change.

8 citations