Mag. José Antonio Brenes Carranza

Mag. José Antonio Brenes Carranza

Es estudiante: 
Si
Programa en que estudia: 
Licenciatura en Ingeniería Industrial

Formación académica

Febrero 2017
Cisco Networking Academy.
Cursando Introducción a la ciberseguridad.
Modalidad online.
 
Diciembre 2016
Universidad de Costa Rica, 
Sistema de Estudios de Posgrado,
Maestría Profesional en Computación e Informática,
 
Enero  – Setiembre 2016
Universidad de Costa Rica,
Cisco Networking Academy.
Cisco Certified Network Analyst, CCNA Módulos 1-4 aprobados.
 
Mayo - Junio 2016
Microsoft México,
Certificación en Microsoft Azure.
“Adopción de Microsoft Azure en Workloads de Open Source”
 
2016
Universidad de Costa Rica, 
Facultad de Ingeniería,
Escuela Ciencias de la Computación e Informática,
Plan de estudios completado. En elaboración de tesis de Licenciatura en Computación e Informática.
 
2016
Universidad de Costa Rica,
Facultad de Ingeniería,
Escuela de Ingeniería Industrial,
Cursando Licenciatura en Ingeniería Industrial.
 
Octubre - Diciembre 2015
Greencore Solutions SRL,
Administración de PostgreSQL.
Curso de aprovechamiento.
 
Abril 2012
Universidad de Costa Rica,
Escuela de Ciencias de la Computación e Informática, 
Bachillerato  en  Ciencias  de  la  Computación  e   Informática.
 
2011
TecApro S.A. 
Certificación Analista Genexus X Evolution I
 
2010
Universidad de Costa Rica, 
Cisco Networking Academy. 
Cisco IT Essentials.

Experiencia laboral

Noviembre - Diciembre 2016
Fundación Promotora de la VIvienda (FUPROVI)
Asesoría para creación de un Plan Estratégico de Migración de Procesos y Servicios de TI a la Nube.
Consultor
 
Enero 2012 – Diciembre 2016
Universidad de Costa Rica, Observatorio Urbano de la Gran Área Metropolitana
Administrador web.
 
Enero 2010 – Diciembre 2016
Universidad de Costa Rica, Programa de Investigación en Desarrollo Urbano Sostenible
Administrador de Tecnologías de Información (RID-UCR)
 
Setiembre 2016-Octubre 2016
ICICOR S.A.
Consultoría para el desarrollo de dos aplicaciones móviles Android para inventariado de activos y levantamiento de personal y áreas de trabajo en el Banco Popular y de Desarrollo Comunal.
Consultor / Desarrollador Android.
 
Agosto 2014-Agosto 2016
ICICOR S.A.
Consultoría para la implementación de un Sistema Integrado de Gestión de Avalúos de bienes muebles e inmuebles.
Consultor / Desarrollador web.
 
Septiembre – Diciembre 2015
Desarrollo del nuevo sitio web del Ministerio de Ciencia, Tecnología y Telecomunicaciones (MICITT).
Consultor / Desarrollador web.
 
Noviembre 2013 – Junio 2015
Universidad de Costa Rica, Oficina de Divulgación e Información. Colaboración en actualización de sitio web institucional. 
Desarrollo de módulo de mapas web institucionales.
Consultor / Desarrollador web.

Proyectos

Publicaciones

Typifying Data Required for the Development of Smart Agriculture Systems

Descripción:

Smart agriculture is an active research field. Currently, many researchers are working on the construction of platforms directed to improve efficiency, crop processes, and data awareness. However, it is common that developers focus on data monitoring instead of the data relevance for decision making or the costs associated with the creation of monitoring platforms. In this paper, we present a classification of the data required by researchers on the construction of decision-support systems applied to smart agriculture processes. By using this classification, the user can define which data are relevant according to the characteristics of the problem that needs to be solved.We have applied the classification to data recollected in a study case conducted by the end of last year. Besides, we identify a list of agronomic and climatic variables commonly used in the construction of decision support systems. We apply the classification to this list of variables as an example for researchers. As a conclusion, this typification permits the researcher to identify data that has to be monitored and controlled, and data that does not have to be measured, the later based on the data characteristics and utility for the farmer.

Tipo de publicación: Conference Paper

Publicado en: 2019 IV Jornadas Costarricenses de Investigación en Computación e Informática (JoCICI)

Decision support systems that use artificial intelligence for precision agriculture: a systematic literature mapping

Descripción:

Decision support systems for agriculture allow to optimize crop processes by using the least amount of resources (land, water and fertilizers). In this study, we characterized decision support systems that use artificial intelligence (AI) techniques for precision agriculture processes. A total of 12 artificial intelligence techniques and 73 input variables were identified, with climate variables being the most used. Keywords: decision support systems; artificial intelligence; precision agriculture; greenhouses.

Tipo de publicación: Journal Article

Publicado en: Revista Ibérica de Sistemas e Tecnologias de Informação

Early Detection of Diseases in Precision Agriculture Processes Supported by Technology

Descripción:

One of the biggest challenges for farmers is the prevention of disease appearance on crops. Governments around the world control border product entry to reduce the number of foreign diseases affecting local producers. Evenmore, it is also important to reduce the spread of crop diseases as quickly as possible and in early stages of propagation, to enable farmers to attack them on time, or to remove the affected plants. In this research, we propose the use of convolutional neural networks to detect diseases in horticultural crops. We compare the results of disease classification in images of plant leaves, in terms of performance, time execution, and classifier size. In the analysis, we implement two distinct classifiers, a densenet-161 pre-trained model and a custom created model. We concluded that for disease detection in tomato crops, our custom model has better execution time and size, and the classification performance is acceptable. Therefore, the custom model could be useful to use to create a solution that helps small farmers in rural areas in resource-limited mobile devices.

Tipo de publicación: Book Chapter

Publicado en: Advances in Sustainability Science and Technology

When One Wireless Technology is Not Enough: A Network Architecture for Precision Agriculture Using LoRa, Wi-Fi, and LTE

Descripción:

The world population will reach nearly 10 billion people by 2050, according to the United Nations. Therefore, more food to supply the world's demand will be required in the following years. Precision agriculture emerges as an option to satisfy the growing demand. In smart farming, wireless sensor networks (WSNs) are crucial in the deployment of sensors in crop fields. Precision agriculture includes crop monitoring and fertigation control. Monitoring and control have distinct network requirements. While monitoring stations deployment requires long-range networks, control stations have other requirements like low latency. For that reason, the use of a combination of WSN is necessary. In this paper, we present an option of network architecture for precision agriculture projects. The architecture includes the use of LoRa for monitoring stations and Wi-Fi/LTE for control stations. Currently, we are working on smart fertigation in greenhouses. For the architecture, we consider the typical requirements for smart farming projects, but also our project’s requirements.

Tipo de publicación: Conference Paper

Publicado en: Intelligent Sustainable Systems

Designing a Context-Aware Smart Notifications System for Precision Agriculture

Descripción:

Smart farming solutions seek to help farmers in their daily activities. Their use has shown that it is beneficial for farmers to be aware of the distinct variables affecting the production. For this reason, having alerts and notifications in monitoring and control platforms is crucial. However, in some circumstances, farmers cannot attend to the messages delivered through traditional mechanisms, making it impossible for them to be informed at the right moment. In this paper, we present the design evaluation of an intelligent context-aware smart notifications system for precision agriculture. We consider using distinct notification mechanisms to improve the delivery of notifications to the farmers. We carry out an anticipated user experience evaluation to assess the system’s design and validate the use of the notification mechanisms in distinct scenarios. A total of 48 potential users from Spain and Costa Rica participated in the evaluation. The results show that our proposed system can be very helpful in supporting farmers to be aware of the state of crops. In addition, non-traditional notification mechanisms can potentially keep the farmers informed without affecting their daily activities. Costa Rican potential users value the system’s novelty more than Spanish users.

Tipo de publicación: Conference Paper

Publicado en: Proceedings of the International Conference on Ubiquitous Computing Ambient Intelligence (UCAmI 2022)

User - Smart Building Interactions: An Analysis of Privacy and Productivity Human Factors

Descripción:

Smart buildings are increasingly becoming more common and changing the way we interact with our home, workplace, and cities. Consequently, it is important to study how human factors play a role in smart building-based environments. This research focuses on the privacy and productivity of human factors, and presents the results of two complementary evaluations: a survey in which people’s privacy concerns were analyzed and an assessment that quantifies if smart building functionalities impacts people’s productivity.

Tipo de publicación: Conference Paper

Publicado en: Proceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022)

Usability assessment of a greenhouse context-aware alert system for small-scale farmers

Descripción:

In the dynamic landscape of modern agriculture, integrating technology holds immense potential to enhance efficiency and productivity for small-scale farmers. This study presents a user-centric evaluation of an intelligent context-aware alert system, tailored for small-scale greenhouse farming. We employed standardized questionnaires, including the NASA Task Load Index and the User Experience Questionnaire, to assess the system's perceived utility, mental workload, and overall user experience. Our findings reveal the high perceived utility of the system among farmers. Farmers participating in the assessment indicated a strong intention to utilize the system for crop monitoring. Moreover, the system demonstrated a moderate mental workload, suggesting ease of use and potential acceptance by users. Our evaluation highlighted an excellent user experience, with scores ranging from very good to extremely good across all dimensions. Furthermore, user preferences for alert mechanisms underscored the importance of adaptable notifications, with voice and text alerts favored for comprehensive information dissemination. Light and voice alerts were preferred during manual tasks. This study highlights the significance of user-centered design in agricultural technology, offering insights to enhance the usability and the adoption of alert systems in small-scale farming environments. The positive reception of the system's utility and the moderate mental workload suggest that such technology can be readily adopted by farmers, thereby improving monitoring and management practices in greenhouse farming. The preference for adaptable alert mechanisms further emphasizes the need for flexible and context-sensitive solutions in agricultural technology.

Tipo de publicación: Journal Article

Publicado en: Front. Comput. Sci.