This thesis proposes hardware and software security enhancements to the robotic explorer of a capstone team, in collaboration with the NASA Psyche Mission Student Collaborations program. The NASA Psyche Mission, launching in 2022 and reaching the metallic asteroid of the same name in 2026, will explore from orbit what is hypothesized to be remnant core material of an early planet, potentially providing key insights to planet formation. Following this initial mission, it is possible there would be scientists and engineers interested in proposing a mission to land an explorer on the surface of Psyche to further document various properties of the asteroid. As a proposal for a second mission, an interdisciplinary engineering and science capstone team at Arizona State University designed and constructed a robotic explorer for the hypothesized surfaces of Psyche, capable of semi-autonomously navigating simulated surfaces to collect scientific data from onboard sensors. A critical component of this explorer is the command and data handling subsystem, and as such, the security of this system, though outside the scope of the capstone project, remains a crucial consideration. This thesis proposes the pairing of Trusted Platform Module (TPM) technology for increased hardware security and the implementation of SELinux (Security Enhanced Linux) for increased software security for Earth-based testing as well as space-ready missions.

Radiation hardening of electronic devices is generally necessary when designing for the space environment. Non-volatile memory technologies are of particular concern when designing for the mitigation of radiation effects. Among other radiation effects, single-event upsets can create bit flips in non-volatile memories, leading to data corruption. In this paper, a Verilog implementation of a Reed-Solomon error-correcting code is considered for its ability to mitigate the effects of single-event upsets on non-volatile memories. This implementation is compared with the simpler procedure of using triple modular redundancy.

Every communication system has a receiver and a transmitter. Irrespective if it is wired or wireless.The future of wireless communication consists of a massive number of transmitters and receivers. The question arises, can we use computer vision to help wireless communication? To satisfy the high data requirement, a large number of antennas are required. The devices that employ large-antenna arrays have other sensors such as RGB camera, depth camera, or LiDAR sensors.These vision sensors help us overcome the non-trivial wireless communication challenges, such as beam blockage prediction and hand-over prediction.This is further motivated by the recent advances in deep learning and computer vision that can extract high-level semantics from complex visual scenes, and the increasing interest of leveraging machine/deep learning tools in wireless communication problems.[1] <br/><br/>The research was focused solely based on technology like 3D cameras,object detection and object tracking using Computer vision and compression techniques. The main objective of using computer vision was to make Milli-meter Wave communication more robust, and to collect more data for the machine learning algorithms. Pre-build lossless and lossy compression algorithms, such as FFMPEG, were used in the research. An algorithm was developed that could use 3D cameras and machine learning models such as YOLOV3, to track moving objects using servo motors and low powered computers like the raspberry pi or the Jetson Nano. In other words, the receiver could track the highly mobile transmitter in 1 dimension using a 3D camera. Not only that, during the research, the transmitter was loaded on a DJI M600 pro drone, and then machine learning and object tracking was used to track the highly mobile drone. In order to build this machine learning model and object tracker, collecting data like depth, RGB images and position coordinates were the first yet the most important step. GPS coordinates from the DJI M600 were also pulled and were successfully plotted on google earth. This proved to be very useful during data collection using a drone and for the future applications of position estimation for a drone using machine learning. <br/><br/>Initially, images were taken from transmitter camera every second,and those frames were then converted to a text file containing hex-decimal values. Each text file was then transmitted from the transmitter to receiver, and on the receiver side, a python code converted the hex-decimal to JPG. This would give an efect of real time video transmission. However, towards the end of the research, an industry standard, real time video was streamed using pre-built FFMPEG modules, GNU radio and Universal Software Radio Peripheral (USRP). The transmitter camera was a PI-camera. More details will be discussed as we further dive deep into this research report.

Automated vehicles are becoming more prevalent in the modern world. Using platoons of automated vehicles can have numerous benefits including increasing the safety of drivers as well as streamlining roadway operations. How individual automated vehicles within a platoon react to each other is essential to creating an efficient method of travel. This paper looks at two individual vehicles forming a platoon and tracks the time headway between the two. Several speed profiles are explored for the following vehicle including a triangular and trapezoidal speed profile. It is discovered that a safety violation occurs during platoon formation where the desired time headway between the vehicles is violated. The aim of this research is to explore if this violation can be eliminated or reduced through utilization of different speed profiles.

Lossy compression is a form of compression that slightly degrades a signal in ways that are ideally not detectable to the human ear. This is opposite to lossless compression, in which the sample is not degraded at all. While lossless compression may seem like the best option, lossy compression, which is used in most audio and video, reduces transmission time and results in much smaller file sizes. However, this compression can affect quality if it goes too far. The more compression there is on a waveform, the more degradation there is, and once a file is lossy compressed, this process is not reversible. This project will observe the degradation of an audio signal after the application of Singular Value Decomposition compression, a lossy compression that eliminates singular values from a signal’s matrix.

Enzyme-induced carbonate precipitation (EICP) is a biocementation technique that produces comparatively fewer carbon dioxide emissions than traditional cementation. However, the use of synthetic reagents for EICP is costly, and the process produces an ammonium byproduct which is a harmful pollutant. This study utilizes fresh urine as a source of urea and calcium-rich zeolites as an ammonium adsorbent and a source of calcium ions for the EICP cementation technique. Batch hydrolysis and adsorption experiments were conducted to determine the effects of zeolite type, zeolite form, and solution composition on ammonium adsorption and calcium release. Cementation experiments were then conducted to determine the effects of different hydrolysis and adsorption times on ammonium adsorption and calcium carbonate precipitation. The results showed that calcium-rich chabazite could be used as a source of calcium ions and as an effective adsorbent of ammonium for EICP. Additionally, synthetic, fresh urine and real, fresh urine had comparable ammonium adsorption and calcium release trends. Finally, inclusion of a pre-hydrolysis step reduced the ammonium adsorption and calcium release, but longer adsorption times lead to calcium carbonate precipitation outside of the sand column, which is an undesirable outcome for soil biocementation; even with this limitation, the calcium carbonate content of sand columns ranged from 0.48% to 0.92%, which signifies the potential of the proposed process for cementation, given a higher initial concentration of urea.

Self-efficacy in engineering, engineering identity, and coping in engineering have been shown in previous studies to be highly important in the advancement of one’s development in the field of engineering. Through the creation and deployment of a 17 question survey, undergraduate and first year masters students were asked to provide information on their engagement at their university, their demographic information, and to rank their level of agreement with 22 statements relating to the aforementioned ideas. Using the results from the collected data, exploratory factor analysis was completed to identify the factors that existed and any correlations. No statistically significant correlations between the identified three factors and demographic or engagement information were found. There needs to be a significant increase in the data sample size for statistically significant results to be found. Additionally, there is future work needed in the creation of an engagement measure that successfully reflects the level and impact of participation in engineering activities beyond traditional coursework.

Is there a mismatch between urban farmers’ perceptions of their farm’s environmental sustainability and its actual environmental impact? Focusing on the use of water and nutrients on each farm as described by the farmers through interviews, it is evident that there is some level of disconnect between ideals and practices. This project may aid in bridging the gap between the two in regard to the farmers’ sustainability goals. This project will move forward by continuing interviews with farmers as well as collecting soil and water from the farms in order to more accurately quantify the sustainability of the farms’ practices. This project demonstrates that there is some degree of misalignment between perception and reality. Two farms claimed they were sustainable when their practices did not reflect that, while 2 farms said they were not sure if they were sustainable when their practices indicated otherwise. Samples from two farms showed high concentrations of nutrients and salts, supporting the idea that there may be a mismatch between perceived and actual sustainability.

This study investigated the difference in biofilm growth between pristine polypropylene microplastics and aged polypropylene microplastics. The microplastics were added to Tempe Town Lake water for 4 weeks. Each week the microplastic biofilms were quantified. Comparing the total biofilm counts, the results showed that the aged microplastic biofilms were larger than the pristine each week. By week 3 the aged microplastic counts had almost doubled in size increasing from 324 to 626 Colony Forming Units per gram in just one week. There was a significant difference in the diversity found from week 1 to week 4. About 40% of the diversity for the pristine microplastic biofilm was seen as light-yellow dots and about 60% of these dots were seen on the aged microplastic biofilms in both weeks. As the microplastics were submerged in the lake water, new phenotypes emerged varying from week 1 to week 4 and from pristine to aged microplastic biofilms. Generally, it was found that as the microplastics stay in the environment there is more biofilm on the particles. The aged microplastics have a larger amount of biofouling, and the pristine microplastic biofilms were found to have more diversity of phenotypes.