A wireless sensor node (WSN) system, capable of sensing animal motion and transmitting motion data wirelessly, is an effective and efficient way to monitor pigs' activity. However, the raw sensor data sampling and transmission consumes lots of power such that WSNs' battery have to be frequently charged or replaced. The proposed work solves this issue through WSN edge computing solution, in which a Random Forest Classifier (RFC) is trained and implemented into WSNs. The implementation of RFC on WSNs does not save power, but the RFC predicts animal behavior such that WSNs can adaptively adjust the data sampling frequency to reduce power consumption. In addition, WSNs can transmit less data by sending RFC predictions instead of raw sensor data to save power. The proposed RFC classifies common animal activities: eating, drinking, laying, standing, and walking with a F-1 score of 93%. The WSN power consumption is reduced by 25% with edge computing intelligence, compare to WSN power that samples and transmits raw sensor data periodically at 10 Hz. / Master of Science / A wireless sensor node (WSN) system that detects animal movement and wirelessly transmits this data is a valuable tool for monitoring pigs' activity. However, the process of sampling and transmitting raw sensor data consumes a significant amount of power, leading to frequent recharging or replacement of WSN batteries. To address this issue, our proposed solution integrates edge computing into WSNs, utilizing a Random Forest Classifier (RFC). The RFC is trained and deployed within the WSNs to predict animal behavior, allowing for adaptive adjustment of data sampling frequency to reduce power consumption. Additionally, by transmitting RFC predictions instead of raw sensor data, WSNs can conserve power by transmitting less data. Our RFC can accurately classify common animal activities, such as eating, drinking, laying, standing, and walking, achieving an F-1 score of 93%. With the integration of edge computing intelligence, WSN power consumption is reduced by 25% compared to traditional WSNs that periodically sample and transmit raw sensor data at 10 Hz.

This thesis aims to develop an e-health embedded system with a real-time operating system (RTOS), which allows users to monitor their body condition, including heart rate and breath, through Bluetooth Low Energy (BLE). Meanwhile, the device is also able to provide guidance for breathing by simulating breathing according to given parameters. In practice, the system samples the heart rate every two milliseconds. To ensure reliability and validity, results are expected to be sent in realtime. However, numerous data cannot be transmitted directly without being processed. Otherwise, the system will crash, and hard faults will occur. A general idea to solve this problem is to classify messages into two categories based on the priority. One is urgent, and the other is unimportant. Two solutions are proposed, one using a unidirectional linked list, and the second using queues. Based on an ARM micro-controller, the e-health embedded system is designed and implemented successfully. The evaluation results show that the solution using a linked list is suitable for the system, while the solution using queues is unable to solve the problem. With the help of the message classification, the urgent messages can be timely transmitted with continuous data. / Avhandlingen syftar till att utveckla ett e-hälso-inbyggt system med ett realtidsoperativsystem (RTOS), som gör det möjligt för användare att övervaka sitt kroppstillstånd, inklusive hjärtfrekvens och andetag, genom Bluetooth Low Energy (BLE). Samtidigt kan enheten också ge vägledning för andning genom att simulera andning enligt givna parametrar. I praktiken samplar systemet hjärtfrekvensen varannan millisekund. För att säkerställa tillförlitlighet och giltighet bör resultaten skickas i realtid. Annars kraschar systemet och allvarliga fel uppstår. En allmän idé för att lösa detta problem är att klassificera meddelanden i två kategorier baserade på prioritering, en är brådskande och den andra är obetydlig. Två lösningar föreslås, en med hjälp av riktad länkad lista och en annan implementerad med hjälp av köer. Resultatmässigt, baserat på en ARM-mikrokontroller, är det inbyggda e-hälsosystemet framgångsrikt designat och konfigurerat. Lösningen med en länkad lista är lämplig för systemet, medan lösningen som implementeras med köer fortfarande inte kan lösa problemet. Med hjälp av meddelandeklassificeringen är de brådskande meddelandena inte ens försenade med kontinuerlig data.

Bluetooth Mesh networks have gained popularity across various industries, showcasing their significant impact on network solutions. This technology is particularly notable for its low power consumption, making it a preferred choice for efficient and sustainable network development.  The objective of this study investigates the behavior of Bluetooth Mesh networks in various environments, aiming to improve network performance and provide guidance for optimal network design. This was achieved by performing experiments in multiple environments.  Data collection and regression analysis along with comparative visualization were employed to understand the relationship between these variables, including distance, number of packets sent, environment, latency, and packet loss ratio.   The results showed a significant relationship between distance and latency in the office and forest environments, as well as between distance and packet loss ratio in all environments. The number of packets sent has impact on latency and packet loss ratio.  The findings contribute to the development of more reliable and efficient communication systems for Internet of Things applications, as well as providing insights into the performance characteristics of the Bluetooth Mesh network in various scenarios.

Mobile technology is developing quickly and becomming a part of daily life and communication. Bluetooth Low Energy is presented as a new way of mobile interaction. However there are not enough studies in this field on the interaction between mobile devices and the physical world. In order to understand user needs, and to encourage users to interact, we simulated an interaction process through designing and testing a prototype in a specific indoor environment. Prototype effectiveness and main characteristics for future mobile application was evaluated through a qualitative user study with 20 participants who interacted with our prototype. / Den mobila tekniken växer snabbt och blir en del av våra liv och vår kommunikation. BLE presenteras på ett nytt sätt inom mobilinteraktion. Det förekommer inte tillräckligt med studier inom området för interaktionen mellan mobila enheter och den fysiska världen. För att förstå användarbehov och få användare att interagera har vi simulerat en interaktiv process genom att designa och testa en prototyp i en specifik inomhusmiljö. Utvärdering av prototypens effektivitet och heuristiken har evaluerats genom en kvalitativ studie med 20 användare som har deltagit i interaktionen med vår prototyp.