The increasing complexity and novel features of industrial robots have made their selection for specific applications a challenging task. Decision-makers are faced with the daunting task of navigating through various attributes and specifications, often under conditions of ambiguity and uncertainty. To assist in this complex decision-making process, this paper introduces a novel decision-making framework based on probabilistic uncertain linguistic q-rung orthopair fuzzy sets (PULq-ROFS). This framework effectively combines the strengths of probabilistic uncertain linguistic term set (PULTS) and q-rung orthopair fuzzy set (q-ROFS) to provide a more robust approach for handling ambiguity and uncertainty in the robot selection process. The proposed methodology integrates a multi-attribute group decision-making (MAGDM) approach. This approach utilizes the VIseKriterijumska Optimizacija I KOmpromisno Resenje (VIKOR) method in conjunction with the criterion importance via inter-criteria correlation (CRITIC) method. The CRITIC method determines attribute weights by analyzing both the differences and contrast intensity of criteria, thereby accounting for the relative strength and conflict among them. VIKOR is then employed to aggregate individual regret and group utility, resulting in a compromise solution that guides decision-makers toward the optimal robot selection. Proposed method provide the clarity and confidence to decision makers for choice of attributes and crediting this enhancement to the framework’s transparency and its ability to incorporate a wide range of stakeholder perspectives. This framework facilitates a more inclusive decision-making process that acknowledges differing viewpoints and preferences. This proposed approach not only directs users toward optimal selections but also encourages collaboration among decision-makers, promoting a sense of shared ownership and responsibility in the selection process. This paper select the best robot by utilizing the benefits of both CRITIC and VIKOR method. The effectiveness of this integrated approach is validated through parameter and comparative analysis. The results demonstrate the potential applicability of the proposed methodology in real-world industrial robot selection scenarios, providing decision-makers with a powerful tool to navigate the complexities of modern robotic systems.

Today, through the monitoring of agronomic variables, the wireless sensor networks are playing an increasingly important role in precision agriculture. Among the emerging technologies used to develop prototypes related to wireless sensor network, we find the Arduino platform and XBee radio modules from the DIGI Company. In this article, based on field tests, we conducted a comparative analysis of received strength signal intensity levels, calculation of path loss with “log-normal shadowing” and free-space path loss models. In addition, we measure packet loss for different transmission, distances and environments with respect to an “Arduino Mega” board, and radio modules XBee PRO S1 and XBee Pro S2. The tests for the packet loss and received strength signal intensity level show the best performance for the XBee Pro S2 in the indoor, outdoor, and rural scenarios.

En Barranquilla, Colombia el riesgo de muerte de personas y pérdidas materiales asociadas con las inundaciones repentinas en las calles de la ciudad es alta. Por ello, el presente artículo muestra el diseño de una arquitectura de red de sensores inalámbricos o WSN (Wireless Sensor Network) para monitorear en tiempo real parámetros atmosféricos que influyen en la detección del nivel de peligrosidad de inundaciones repentinas o los llamados familiarmente "arroyos", producto de las súbitas e intensas lluvias en un breve período de tiempo. El diseño de la red se hizo por medio de un estudio de sitio o site survey para obtener los datos y resultados que son usados en el presente trabajo. Se ha desarrollado también una aplicación web móvil que utiliza el lenguaje unificado de modelado (UML®) basado en un listado de requerimientos que muestra en tiempo real, sobre un mapa de las calles de la ciudad el nivel de peligrosidad del arroyo en diferentes puntos de su trayectoria. El sistema diseñado será de utilidad para la toma de decisiones preventivas por parte del usuario final y, además, está desarrollado para que sea replicable y escalable en entornos similares. Además, en este trabajo se ha probado la plataforma Waspmote y los módulos XBee-PRO ZB (S2) como herramienta tecnológica para la WSN.