This thesis deals with the decentralized autonomous system, in which individual nodes acting like peers, communicate and participate in collaborative tasks and decision making processes. An experimental test-bed is created using four Garcia robots. The robots act like peers and interact with each other using user datagram protocol (UDP) messages. Each robot continuously monitors for messages coming from other robots and respond accordingly. Each robot broadcasts its location to all the other robots within its vicinity. Robots do not have built-in global positioning system (GPS). So, an indoor localization method based on signal strength is developed to estimate robot's position. The signal strength that the robot gets from the nearby wireless access points is used to calculate the robot's position. Trilateration and fingerprint are some of the indoor localization methods used for this purpose. The communication functionality of the decentralized system has been tested and verified in the autonomous systems laboratory.

This thesis investigates the design and implementation of turbo codes over the GNU radio. The turbo codes is a class of iterative channel codes which demonstrates strong capability for error correction. A software defined radio (SDR) is a communication system which can implement different modulation schemes and tune to any frequency band by means of software that can control the programmable hardware. SDR utilizes the general purpose computer to perform certain signal processing techniques. We implement a turbo coding system using the Universal Software Radio Peripheral (USRP), a widely used SDR platform from Ettus. Detail configuration and performance comparison are also provided in this research.

Currently, standards from government agencies such as the National Institute for Occupation Safety and Health exist to aid in safeguarding individuals’ capacity for hearing, but only in factory settings in which large machines often produce loud levels of sound. Neglecting the fact that these preventative measures are only in place in the most limited of settings, no system currently exists to observe and report sound exposure levels in a manner timely or easily recognizable enough to adequately serve its purpose of hearing conservation. Musicians may also incur significant levels of risk for hearing loss in their day-to-day rehearsals and concerts, from high school marching bands to university wind bands. As a result, music school accrediting organizations such as the National Association of Schools of Music and even the European Union have begun taking steps meant to determine the risks associated with music. To meet these goals and improve upon current technologies, a system has been developed that electronically records sound levels utilizing modern hardware, increases the speed of reporting by transmitting data over computer networks and the Internet, and displays measures calculated from these data in a web browser for a highly viewable, user-friendly interface.

The major advantages of radio frequency identification (RFID) technology over barcodes are that the RFID-tagged objects do not require to be in line-of-sight with the reader for their identification and multiple objects can be read simultaneously. But when multiple objects are read simultaneously there is always a problem of collision which reduces the efficiency of the system. This thesis presents a comprehensive study of the dynamic framed slotted ALOHA (DFSA)-based anti-collision multi-tag identification algorithms for passive RFID system. Performance of various DFSA algorithms is compared through extensive simulation results. In addition, a number of simple performance improvement techniques have also been investigated in this thesis, including improved estimation techniques for the number of tags in each read cycle and a low-complexity heuristic stopping criterion that can be easily implemented in the practical system.