Organizations, companies and start-ups need to cope with constant changes on the market which are difficult to predict. Therefore, the development of new systems to detect significant future changes is vital to make correct decisions in an organization and to discover new opportunities. A system based on business intelligence techniques is proposed to detect weak signals, that are related to future transcendental changes. While most known solutions are based on the use of structured data, the proposed system quantitatively detects these signals using heterogeneous and unstructured information from scientific, journalistic and social sources, applying text mining to analyze the documents and natural language processing to extract accurate results. The main contributions are that the system has been designed for any field, using different input datasets of documents, and with an automatic classification of categories for the detected keywords. In this research paper, results from the future of remote sensors are presented. Remote sensing services are providing new applications in observation and analysis of information remotely. This market is projected to witness a significant growth due to the increasing demand for services in commercial and defense industries. The system has obtained promising results, evaluated with two different methodologies, to help experts in the decision-making process and to discover new trends and opportunities.

Quantum computing is a new paradigm for a multitude of computing applications. This study presents the technologies that are currently available for the physical implementation of qubits and quantum gates, establishing their main advantages and disadvantages and the available frameworks for programming and implementing quantum circuits. One of the main applications for quantum computing is the development of new algorithms for machine learning. In this study, an implementation of a quantum circuit based on support vector machines (SVMs) is described for the resolution of classification problems. This circuit is specially designed for the noisy intermediate-scale quantum (NISQ) computers that are currently available. As an experiment, the circuit is tested on a real quantum computer based on superconducting qubits for an application to detect weak signals of the future. Weak signals are indicators of incipient changes that will have a future impact. Even for experts, the detection of these events is complicated since it is too early to predict this impact. The data obtained with the experiment shows promising results but also confirms that ongoing technological development is still required to take full advantage of quantum computing.

Actualmente, una de las mayores amenazas para las empresas es no ser capaces de hacer frente a los cambios constantes que se dan en el mercado, por no predecirlos con la suficiente antelación. Por ello, el desarrollo de nuevos procesos que faciliten la detección de fenómenos y cambios futuros significativos es una componente clave para una correcta toma de decisiones que marque un rumbo correcto para la empresa. Por esta razón, se propone un sistema basado en una arquitectura de inteligencia de negocio que permite detectar cambios discretos o señales débiles (weak signals) en el presente, pero que son indicativos de fenómenos más significativos y cambios trascendentales en el futuro. Frente a los trabajos actuales que se centran en fuentes de información estructuradas, o como mucho, con un único tipo de fuente de datos, en este trabajo la detección de estas señales se realiza de forma cuantitativa a partir de documentos heterogéneos y no estructurados de diversa índole (artículos científicos, periodísticos y redes sociales) sobre los que se aplican técnicas de minería de textos. El sistema ha sido testeado para estudiar el futuro del sector de los paneles solares, habiéndose obtenido resultados prometedores para ayudar a expertos en el reconocimiento de nuevos factores de peso en sus mercados y en el desarrollo de nuevas oportunidades.

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