Self-stabilizing systems can be found in many contexts. They are used in aircraft and camera gimbals to name a few. In this project, a self-stabilizing container was constructed. The construction consists of three parts. An inner ring which rotates around the Z-axis, an outer ring which rotates around the Y-axis and a handle with space for three DC motors and a microcontroller. In this project an Arduino Nano was used. To detect inclination an IMU (Inertial Measurement Unit) was deployed. An IMU is a sensor consisting of three gyroscopes and three accelerometers, one for each coordinate axis. The software for the construction consists of four parts; angle reading, a Kalman filter, two PID-controllers and a motor controller. When a container is inserted into the construction the four-part system keeps the container horizontal and stable. Experimental data shows that in 84% of the tests the construction could stabilize the container. / Självstabiliserande system kan man finna i många olika sammanhang. Några exempel på självstabiliserande system är flygplan och kamerastabilisatorer. I detta projekt konstruerades en självstabiliserande behållare. Konstruktionen består av tre delar. En ring som kan rotera runt Z-axeln, en ring som kan rotera runt Y-axeln och ett handtag med plats för likströmsmotorer och mikrokontroller. I detta projekt användes Arduino Nano. För att avläsa vinklarna användes en tröghetsmäatare. En tröghetsmätare är en sensor som består av tre gyroskop och tre accelerometrar, en för varje axel. Mjukvaran i konstruktionen består av fyra delar; vinkelavläsning, ett Kalmanfilter, två PID-regulatorer och motorkontroller. Beroende på vilken vinkel konstruktionen har kommer någon av motorerna att korrigera vinkeln på behållaren. Testerna visade att konstruktionen kunde stabilisera behållaren i 84% av alla tester.

Context. Generally, health monitoring systems are used in hospitals, which are pricey and gigantic. But with the up gradation of sensors and modules, these devices are also available in portable sizes. These devices are divided into different types according to the disease. So, our project aims to provide a device with multiple parameters monitoring with fall detection, and it is budget-friendly.  Objectives. The objective of our project is to provide freedom to users and monitor simultaneously, using IoT and sensors. People with an illness that may be physical or mental, children, and older people with some issues. They are the users of our idea. Generally, they need to be monitored by a person, which is costly and requires endurance. So, the main objective is to monitor the patient’s health condition and alert in an emergency and store the data on the user’s health.  Methods. After a lot of observation, we found that we can monitor the patient’s health status using an ESP32 Wroom dev kit, which is a microcontroller that consists of Bluetooth and Wi-Fi. We use an MPU6050 accelerometer that detects the falling and motion of the user using three axial movements. We use MAX30102 pulse oximetry which measures the oxygen level, pulse rate, and temperature. Along with these, we use a mobile application that receives data and stores it.  Results. The device reads the parameters regularly and stores the data in the cloud or mobile application. It contains a push button that alerts the relatives and respected authorities. It transmits the location. Finally, it will trigger the command of alerting when the user falls. Conclusions. Every person can use our health monitoring system. The person should wear the device properly and be connected to the Wi-Fi. Once the fall is detected, the contacts are notified. And the detection is more accurate. Regular usage of the device increases the accuracy and analysis of the user’s health.

Industrial robotic arms have transformed the manufacturing environment by providing efficient and precise automation solutions. These sophisticated machines, powered by innovative technology, are capable of performing difficult tasks with speed and accuracy. The project described here is related to industrial robotics because it focuses on the creation of a gesture-controlled robotic arm. This project aims to build a robotic arm that can be controlled by gestures utilising MPU6050 sensors and flex sensors. By interpreting gestures acquired by strategically placed sensors, the robotic arm is designed to emulate human arm movements. The MPU6050 sensors are placed on the hand, near the elbow, and near the shoulder, allowing the system to capture the arm’s orientation and movement in real time. The gripper mechanism of the robotic arm is controlled by a flex sensor on the index finger. The central control unit is the Arduino UNO Rev3 SMD microcontroller, which is in charge of analyzing sensor input and translating it into matching robotic arm movements. The suggested system intends to provide a user-friendly and intuitive method for robotic arm control, with possible applications in a variety of domains such as industrial automation, medical support, and prosthetics.