Abstract
Every year forest fires destroy millions of hectares of land worldwide. Detecting forest fire ignition in the early stages is fundamental to avoid forest fires catastrophes. In this approach, Wireless Sensor Network is explored to develop a monitoring system to send alert to authorities when a fire ignition is detected. The study of sensors allocation is essential in this type of monitoring system since its performance is directly related to the position of the sensors, which also defines the coverage region. In this paper, a mathematical model is proposed to solve the sensor allocation problem. This model considers the sensor coverage limitation, the distance, and the forest density interference in the sensor reach. A Genetic Algorithm is implemented to solve the optimisation model and minimise the forest fire hazard. The results obtained are promising since the algorithm could allocate the sensor avoiding overlaps and minimising the total fire hazard value for both regions considered.

Abstract
Teaching based on challenges and competitions is one of the most exciting and promising methods for students. In this paper, a competition of the Portuguese Robotics Open is addressed and a solution is proposed. The Robot@Factory Lite is a new challenge and accepts participants from secondary schools (Rookie) and universities. The concepts of simulation, hardware-in-the-loop and timed finite state machine are presented and validated in the real robot prototype. The aim of this paper is to disseminate the developed solution in order to attract more students to STEM educational program.

Abstract
The collaboration between humans and machines, where humans can share the same work environment without safety equipment due to the collision avoidance characteristic is one of the research topics for the Industry 4.0. This work proposes a system that acquires the space of the environment through an RGB-Depth sensor, verifies the free spaces in the created Point Cloud and executes the trajectory of the collaborative manipulator avoiding collisions. It is demonstrated a simulated environment before the system in real situations, in which the movements of pick-and-place tasks are defined, diverting from virtual obstacles with the RGB-Depth sensor. It is possible to apply this system in real situations with obstacles and humans, due to the results obtained in the simulation. The basic structure of the system is supported by the ROS software, in particular, the MoveIt! and Rviz. These tools serve both for simulations and for real applications. The obtained results allow to validate the system using the algorithms PRM and RRT, chosen for being commonly used in the field of robot path planning.

Abstract
Worldwide, forests have been devastated by fires in recent years. Whe- ther by human intervention or for other reasons, the history of burned areas is increasing year after year, degrading fauna and flora. For this reason, it is vital to detect an early ignition so that firefighters can act quickly, reducing the impacts caused by forest fires. The proposed system aims to improve the nature monitoring and to assist the existing surveillance systems through Wireless Sensor Network. The network formed by the set of sensors has the potential to identify forest ignitions and, consequently, alerts the authorities through LoRaWAN communication. This work presents a prototype based on low-cost technology, which can be used in areas that require a high density of modules. Tests with a Wireless Sensor Network made up of nine prototypes demonstrate its effectiveness and robustness in terms of data transmission and collection. In this way, it is possible to apply this approach in Portuguese forests with a high level of forest fire risk, transforming them into Forests 4.0 concept.

Abstract
Inspection based on mobile autonomous robots can assume an important role in many industries. Instead of having fixed sensors, the concept of assembling the sensors on a mobile robot that performs the scanning and inspection through a defined path is cheaper, configurable and adaptable. This paper describes a mobile robot, equipped with several gas sensors and a LIDAR device, that scans an established area by following a trajectory based on way-points searching for gas leakage and simultaneously avoid obstacles in the map. In other words, the robot follows the trajectory while the gas concentration is under a defined value and surrounding the obstacles. Otherwise, the autonomous robot starts the leakage search based on a search algorithm that allows to find the leakage position. The proposed methodology is verified in simulation based on a model of the real robot. The search test performed in a simulation environment allows to validate the proposed methodology.

Abstract
Industrial robots are a technology which is highly present in industry and can perform several tasks, namely machining activities. Different than CNC machines, which work with G-code and have available several software applications to generate the machine code, there is a lack of software for robotic arms, in addition to each application depending on its own language and software. This work studied a way to use different robotic arms for 3D part machining processes, to perform 3D objects reconstruction obtained through a low-cost 3D scanner. Dealing with the 3D reconstruction by integrating 3D acquisition and robotic milling with software available on the market, this paper presents a system that acquires and reconstructs a 3D object, in order to seek greater flexibility with lower initial investments and checking the applicability of robot arm in these tasks. For this, a 3D object is scanned and imported to a CAD/CAM software, to generate the machining toolpath, and a software application is used to convert the G-code into robot code. Several experiments were performed, using an ABB IRB 2600 robot arm, and the results of the machining process allowed to validate the G-code conversion and milling process using robotic arms, according to the proposed methodology.