This thesis focuses on the design and implementation of the wireless localization module, using UWB technology with emphases on low-power firmwre based on RTOS. Wireless localization is based on TDoA algorithm.  The resulting HW module is designed as a four layer PCB, based on MCU crf52832 (ARM Cortex M4) and UWB module DevaWave DW1000. Firmware is implemented using FreeRTOS with emphasis on low power consumption. For hardware implementation, Eagle CAD was used. Firmware is implemented in C and Assembly programming languages.

The aim of this work is study the standard for wireless sensor networks IEEE 802.15.4a. Design and implementation of a packet analyzer for ultra wideband technology com- pliant with IEEE 802.15.4a standard. Integrate packet analyzer to inspection software Wireshark and implement dissector for view packets. Finally, analyze and evaluate the parameters of the proposed packet analyzer.

The goal for this master thesis is to develop a prototype that uses ultra-wideband (UWB) communications to wirelessly transfer electrocardiogram (ECG) data from an ECG measurement unit to an Android device (smartphone or similar) which is used to process and display the ECG signals. The prototype should consist of two hardware nodes; (1) Node one having a ECG measurement unit (an AD8232 single lead heart rate monitor), an UWB communication module (a Decawave DWM1000 module) and a microcontroller (an Arduino DUE); and (2) Node two having an Android device (an Android smartphone), an UWB communication module (a Decawave DWM1000 module) and a microcontroller (an Arduino DUE). On Node one the AD8232 monitor for ECG measurements is connected to an analog input (with an analog to digital converter (ADC)) on the Arduino and the DWM1000 module is connected to the Arduino via serial peripheral interface (SPI). On Node two the DWM1000 is connected to the Arduino via SPI to receive ECG data from Node one, and the Arduino is connected to the smartphone through a serial USB cable with an USB on-the-go adapter to send the ECG data to the smartphone, where it is filtered and displayed with an Android application. The application has the potential to add, for example, ECG analysis for diagnosing heart activities with artificial intelligence (AI) and further transmit the ECG data for remote medical care. The Arduino is programmed in Arduino IDE (integrated development environment) to handle ECG measurements and UWB communications (transmitting and receiving ECG data), which is limited to a single UWB channel because of limitations of the DWM1000 module. The Android application is created using Android studio, and it can process (with a notch filter) and display 1-12 channel ECG. The prototype has been built and tested. The results show that a single lead ECG measurement can be sent via UWB communication to a smartphone to display in real time. Multiple data channels (1-12 analog inputs on the Arduino) can be multiplexed, transmitted and displayed in real time. This thesis concludes that UWB has huge development potential, and will likely be used for various wireless devices in the future.