The 4th Industrial Revolution encouraged the emergence of new robotic solutions and advancements to assist human operators and increase efficiency and safety within all industrial environments, such as energy sectors, automotive, aerospace, indoor agriculture and so on. Therefore, research in this direction is fueled by the constant need of intelligent systems that can fulfill specific needs throughout industries, such as real-time assessment and report concerning equipment and environment. For example, the indoor-agriculture industry needs robotic systems able to provide data regarding the crop growth environment and plant healthcare in real-time remotely and on-site. In addition to this, manufacturing and energy industries are in need of assessing in real-time equipment, such as manufacture equipment, control and electrical panels, turbines, power lines to ensure the safety and efficiency of the industrial environment. Thus, the proposed solution is a compact and mobile sensorial robotic platform that can accommodate a wide range of devices, such as RGB, IR, multispectral and stereoscopic imaging cameras, and sensors, such as air-quality, environmental, smoke, Geiger and so on. Another key-aspect is the possibility of remote operation via Internet. In order to accommodate the wide range of integrated sensors an open-source and modular software framework was used, ROS (Robot Operating System). This approach allows multiple sensors and devices to be integrated within a unitary software framework in order to obtain valuable real-time data of the operating environment. Also, sensors can be swapped with minimal software modifications, offering a modular character to the hardware and software system. The proposed solution is suitable in industrial environments, such as manufacturing, automotive, aerospace, indoor agriculture, energy and adjacent environments.

The large-scale deployment of electric buses and trolleybuses in urban public transport requires advanced energy management strategies that consider operational constraints, power-grid interactions, and battery longevity. Digital Twin (DT) technology offers a promising framework to support such strategies, but it depends critically on high-quality real-time data from the physi-cal system. In this regard, this paper proposes a mobile data acquisition (mDAQ) system installed on electric vehicles as a key enabling layer for a Holistic Energy Management System (HEMS). This system collects syn-chronized multiparameter data in electrical, thermal, positional, and operational streams through IoT communication towards DT models that opti-mize charging schedules, energy flows, and preventive maintenance. Its ar-chitecture combines multiplexed sensing, floating differential measurement, Geographic Positioning System (GPS) synchronization, MQTT-based com-munication, and driver-oriented user interfaces. The proposed solution is po-sitioned within an integrated DT-based framework for urban e-mobility and can be deployed in a real public transport operator network.

Accurate estimation of forest structural parameters is essential for precision forestry, carbon stock modelling, and sustainable management. Traditional manual inventories are labor-intensive and often limited by sampling intensity. This paper evaluates the application of the Forest Structural Complexity Tool (FSCT), a robust automated pipeline, for the segmentation and extraction of dendrometric metrics from high-density LiDAR point clouds. We processed data from four distinct plots located in the Postăvaru and Barzava regions using UAV and Mobile Laser Scanning (MLS) data. The study validates the tool's capability to process datasets from varying sensor sources while highlighting current limitations regarding low-resolution Aerial Laser Scanning (ALS). Results indicate successful segmentation across varying stem densities, with a specific focus on the comparative analysis of geometric volume modeling methods.

The Ball and Plate Systems aim to fix a ball at the midpoint of the flat plate by rolling or pitching the plate in the direction of the x and y axes when it moves in any direction on that flat plate due to gravity or an external disturbance source. This study aims to redesign the ball and plate system with a new design and transform it into a laboratory set for use in educational activities.

Ordinary ball and plate systems perform this function using different mechanical methods. The most popular of these is the version driven by ordinary hobby-use servo motors attached to two sides of the flat plate. The primary reason for constructing these training sets in miniature is the use of touch-sensitive plates to detect the ball, and these are not manufactured in any size.

The aim of this study is to provide a more visually appealing training set and to more effectively incorporate servo motors into the theoretical content of the training set. For this reason, the study was conducted with a plate scale of 1000x1000mm. The purpose of the study is to balance the ball in the centre of the plate with different control methods.

Thanks to this study, the ball and plate system was created in a more visual and user-friendly manner. Because the resulting system includes a next-generation controller like PLCnext, it also allows users to test different control algorithms.

In the last decade, the use of automation in the workplace has experienced an exponential rise, enabled by technological improvements, which improve accessibility and enhance adaptability. This shift towards automated workspaces has been made possible by advancements regarding organizational solutions that, simultaneously, facilitate integration into corporate spaces.

The main objective of this project is to improve the performance of organizations, by implementing an internal platform that manages document transfers, both in physical and digital format, maintains the stock of supplies and provides alerts for their unavailability. In order for the application to be efficient and sustainable over an extended period of time, factors such as cost, long-term impact and compatibility with existing processes and practices are carefully analyzed.

A series of algorithms was used, that manages essential functions, such as robot navigation (A*), task customization (Decision Tree) and predictive maintenance (ARIMA). Following the identification of existing deficiencies, an integrated system (InternBot) can be provided as a solution. The InternBot structure has two versions. The exclusively digital version, Digital-InternBot (D-IB), with a reduced cost, offers functionalities such as: personalized task management, priority-based scheduling, anticipation of consumable needs with alerts and automatic orders. The second version, Social-InternBot (S-IB), has a robotic component that takes over time-consuming and repetitive physical tasks, in addition to the digital part.

The results from implementing this complex system, with dual functionality, digital and physical, consist of quick access to information, reduced workload for staff and optimised document flow. Although the system is designed to be efficient, errors such as incorrect document location, confusion between files with similar names or data synchronization problems may occur. These situations are anticipated and will be managed through continuous monitoring and immediate intervention by monitoring staff, thus ensuring the correct and continuous functioning of the proposed smart platform.