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Full-Text Articles in Systems and Communications

Wireless Underground Communications In Sewer And Stormwater Overflow Monitoring: Radio Waves Through Soil And Asphalt Medium, Usman Raza, Abdul Salam Feb 2020

Wireless Underground Communications In Sewer And Stormwater Overflow Monitoring: Radio Waves Through Soil And Asphalt Medium, Usman Raza, Abdul Salam

Faculty Publications

Storm drains and sanitary sewers are prone to backups and overflows due to extra amount wastewater entering the pipes. To prevent that, it is imperative to efficiently monitor the urban underground infrastructure. The combination of sensors system and wireless underground communication system can be used to realize urban underground IoT applications, e.g., storm water and wastewater overflow monitoring systems. The aim of this article is to establish a feasibility of the use of wireless underground communications techniques, and wave propagation through the subsurface soil and asphalt layers, in an underground pavement system for storm water and sewer overflow monitoring application. …

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Iot For Smart Parking, Mohammad Abdellatif, Noura Elshabasy Feb 2020

Iot For Smart Parking, Mohammad Abdellatif, Noura Elshabasy

Electrical Engineering

Nowadays, technology has become more reliable that allowed human interaction to decrease while the machines have started to take over in many fields of interest. The Internet of things (IoT) represents the idea of machines ability to control entire systems without any human interactions. This paper proposes an IoT system that takes a picture of parked cars in a garage, extract the plate number and the location of the car, and places these information in a database. At the garage entrance, a terminal linked to the system allows the user to locate the parked car using the license plate no.. …

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Short-Term Electricity Price Forecasting In Deregulated Electricity Market Based On Enhanced Artificial Intelligence Techniques, Pourdaryaei Alireza Feb 2020

Short-Term Electricity Price Forecasting In Deregulated Electricity Market Based On Enhanced Artificial Intelligence Techniques, Pourdaryaei Alireza

Student Works (2020-2029)

Electricity price forecasting is considered as one of prime factors for operation, planning and scheduling of price-setter market participants. However, possessing time variant, non-linear and non-stationary behaviors make the electricity price a complex signal. The main challenge in this area is providing highly accurate and efficient day-ahead price forecasting. A suitable feature selection technique, which is able to model the interacting features and nonlinearities of the forecast processes, is still required although researches have been performed for day-ahead forecasting. In this research, a hybrid electricity price forecasting methodology is proposed using two-stage feature selection method and optimization using adaptive neuro-fuzzy …

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Improved Estimation For Saleh Model And Predistortion Of Power Amplifiers Using 1-Db Compression Point, Haider Al Kanan, Xianzhen Yang, Fu Li Jan 2020

Improved Estimation For Saleh Model And Predistortion Of Power Amplifiers Using 1-Db Compression Point, Haider Al Kanan, Xianzhen Yang, Fu Li

Electrical and Computer Engineering Faculty Publications and Presentations

This paper proposes an improved estimation approach for modelling RF power amplifiers (PAs) using the Saleh behavioural model. The proposed approach is appropriate for solid-state PA technologies. The 1-dB compression point of the PA is included in the estimation approach to improve the estimation of the Saleh coefficients. Thus, expressions are derived to describe the relationship between the parameters of the Saleh model and the manufacturing specifications of PAs: gain (G), third-order intercept point (IP3) and 1-dB compression point (P1dB). This method is a simple estimation of a memoryless amplitude-to-amplitude (AM/AM) nonlinearity to benefit RF designers …

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Ensemble Lung Segmentation System Using Deep Neural Networks, Redha A. Ali, Russell C. Hardie, Hussin K. Ragb Jan 2020

Ensemble Lung Segmentation System Using Deep Neural Networks, Redha A. Ali, Russell C. Hardie, Hussin K. Ragb

Electrical and Computer Engineering Faculty Publications

Lung segmentation is a significant step in developing computer-aided diagnosis (CAD) using Chest Radiographs (CRs). CRs are used for diagnosis of the 2019 novel coronavirus disease (COVID-19), lung cancer, tuberculosis, and pneumonia. Hence, developing a Computer-Aided Detection (CAD) system would provide a second opinion to help radiologists in the reading process, increase objectivity, and reduce the workload. In this paper, we present the implementation of our ensemble deep learning model for lung segmentation. This model is based on the original DeepLabV3+, which is the extended model of DeepLabV3. Our model utilizes various architectures as a backbone of DeepLabV3+, such as …

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Calibration To Mitigate Near-Field Antennas Effects For A Mimo Radar Imaging System, Ha Hoang, Matthias John, Patrick Mcevoy, Max Ammann Jan 2020

Calibration To Mitigate Near-Field Antennas Effects For A Mimo Radar Imaging System, Ha Hoang, Matthias John, Patrick Mcevoy, Max Ammann

Articles

A calibration method for a high-resolution hybrid MIMO turntable radar imaging system is presented. A line of small metal spheres is employed as a test pattern in the calibration process to measure the position shift caused by undesired antenna effects. The unwanted effects in the antenna near-field responses are analysed, modelled and significantly mitigated based on the symmetry and differences in the responses of the MIMO configuration.

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Enhancing The Performance Of 433 Mhz Underwater Wsn Using Handover Mechanisms., Mohammad Abdellatif, Sameh Abdellatif, Salma M. Maher, Ziad M. Ali Jan 2020

Enhancing The Performance Of 433 Mhz Underwater Wsn Using Handover Mechanisms., Mohammad Abdellatif, Sameh Abdellatif, Salma M. Maher, Ziad M. Ali

Electrical Engineering

Wireless technology has taken part of our daily life which paved the way to underwater wireless communication to flourish as a research area. This research field is important for exploration of the seabed as oceanographers stated that there are still unexplored ocean perceptions. Latency and distance are considered to be the main factors that confronts this particular field and degrades the overall performance. This paper investigates the performance of RF signals in varying water depths. A point to point system was first considered with 2 nodes, the results of this experiment along with our previous work aroused the idea of …

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Cognitive Resource Management In 5g Networks, Kelvin M. Franco-Argueta Jan 2020

Cognitive Resource Management In 5g Networks, Kelvin M. Franco-Argueta

OUR Journal: ODU Undergraduate Research Journal

The 4G LTE network offers a high speed connectivity that is predicated on the construction platform of the 3G network and relies on an Internet Protocol (IP) for data transmission and reception. This platform’s utility is quickly becoming exhausted as the frequency spectrum approaches maximum device connectivity capacity. To improve network capacity, we must expand the bandwidth that our devices operate on. To effectively carry out this task, a self-configurable network must be employed in the development of the 5g network. This article aims to explore the technologies which form the platform for the 5G network and the cognitive resource …

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Corrections To ‘‘Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping’’, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel Jan 2020

Corrections To ‘‘Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping’’, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel

Electrical and Computer Engineering Faculty Publications

In the above article [1], Figure 2 was incorrect. Unfortunately, we mixed the color label of "CONV $\to $ BN $\to $ ReLu" and "Unpooling" in the CNN structure section of Figure 2. The color label of "CONV $\to $ BN $\to $ ReLu" should be orange while the color label of "Unpooling" should be green. Also, the word "Decoder" is misspelled. That same figure with the same error is also used for the graphic abstract. The corrected figure is given here. None of the sections in the figure is modified. The only change is in the color label of …

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A Four-Port Dc-Dc Converter For A Hybrid Wind/Solar Energy System, Jiahong Ning Jan 2020

A Four-Port Dc-Dc Converter For A Hybrid Wind/Solar Energy System, Jiahong Ning

All Graduate Theses, Dissertations, and Other Capstone Projects

With the increasing demand for clean and hybrid energy in the last decades, more and more attentions are paid to the renewable energy, e.g., wind and solar energy. According to the International Energy Agency, solar power was growing-fastest source in the world. In a hybrid wind/solar system, power converters play an important role in in power management and the voltage regulation. Gradually, power systems have undergone a paradigm shift from centralized generation to distributed generation. Smart grid, which is a combination of power systems and communication networks, was proposed to allow power systems to fit the future system challenge. However, …

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Virtual Impedance Based Decentralized Control For A Microgrid System, Ramkrishna Mishan Jan 2020

Virtual Impedance Based Decentralized Control For A Microgrid System, Ramkrishna Mishan

All Graduate Theses, Dissertations, and Other Capstone Projects

As greenhouse gases produced from the conventional power plant causes global climate change, using renewable energy sources (RESs) in the future power system is inevitable. To minimize greenhouse gases emission, the interest in renewable grid or micro-grid is growing nowadays. In the microgrid, especially in AC microgrids, converters play an important role in many areas, including microgrid integration, uninterrupted power supply, and flexible alternating current transmission systems. Inverter plays an essential role in grid integration because it serves the interface between the energy source and the power grid. The important aspect of the inverter is control. This thesis studies several …

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Accurate Range-Based Indoor Localization Using Pso-Kalman Filter Fusion, Paul Bupe Jr Jan 2020

Accurate Range-Based Indoor Localization Using Pso-Kalman Filter Fusion, Paul Bupe Jr

College of Graduate Studies: Theses & Dissertations

Accurate indoor localization often depends on infrastructure support for distance estimation in range-based techniques. One can also trade off accuracy to reduce infrastructure investment by using relative positions of other nodes, as in range-free localization. Even for range-based methods where accurate Ultra-WideBand (UWB) signals are used, non line-of-sight (NLOS) conditions pose significant difficulty in accurate indoor localization. Existing solutions rely on additional measurements from sensors and typically correct the noise using a Kalman filter (KF). Solutions can also be customized to specific environments through extensive profiling. In this work, a range-based indoor localization algorithm called PSO - Kalman Filter Fusion …

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Coverage Guided Differential Adversarial Testing Of Deep Learning Systems, Jianmin Guo, Houbing Song, Yue Zhao, Yu Jiang Jan 2020

Coverage Guided Differential Adversarial Testing Of Deep Learning Systems, Jianmin Guo, Houbing Song, Yue Zhao, Yu Jiang

Publications

Deep learning is increasingly applied to safety-critical application domains such as autonomous cars and medical devices. It is of significant importance to ensure their reliability and robustness. In this paper, we propose DLFuzz, the coverage guided differential adversarial testing framework to guide deep learing systems exposing incorrect behaviors. DLFuzz keeps minutely mutating the input to maximize the neuron coverage and the prediction difference between the original input and the mutated input, without manual labeling effort or cross-referencing oracles from other systems with the same functionality. We also design multiple novel strategies for neuron selection to improve the neuron coverage. The …

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Ev Charging Behavior Analysis Using Hybrid Intelligence For 5g Smart Grid, Yi Shen, Wei Fang, Feng Ye, Michel Kadoch Jan 2020

Ev Charging Behavior Analysis Using Hybrid Intelligence For 5g Smart Grid, Yi Shen, Wei Fang, Feng Ye, Michel Kadoch

Electrical and Computer Engineering Faculty Publications

With the development of the Internet of Things (IoT) and the widespread use of electric vehicles (EV), vehicle-to-grid (V2G) has sparked considerable discussion as an energy-management technology. Due to the inherently high maneuverability of EVs, V2G systems must provide on-demand service for EVs. Therefore, in this work, we propose a hybrid computing architecture based on fog and cloud with applications in 5G-based V2G networks. This architecture allows the bi-directional flow of power and information between schedulable EVs and smart grids (SGs) to improve the quality of service and cost-effectiveness of energy service providers. However, it is very important to select …

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Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel Jan 2020

Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel

Electrical and Computer Engineering Faculty Publications

Rising global temperatures over the past decades is directly affecting glacier dynamics. To understand glacier fluctuations and document regional glacier-state trends, glacier-boundary detection is necessary. Debris-covered glacier (DCG) mapping, however, is notoriously difficult using conventional geospatial technology methods. Therefore, in this research for automated DCG mapping, we evaluate the utility of a convolutional neural network (CNN), which is a deep learning feed-forward neural network. The CNN inputs include Landsat satellite images, an Advanced Land Observation Satellite (ALOS) digital elevation model (DEM) and DEM-derived land-surface parameters. Our CNN based deep-learning approach named GlacierNet was designed by appropriately choosing the type, number …

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Mitosisnet: End-To-End Mitotic Cell Detection By Multi-Task Learning, Md Zahangir Alom, Theus Aspiras, Tarek M. Taha, Tj Bowen, Vijayan K. Asari Jan 2020

Mitosisnet: End-To-End Mitotic Cell Detection By Multi-Task Learning, Md Zahangir Alom, Theus Aspiras, Tarek M. Taha, Tj Bowen, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Mitotic cell detection is one of the challenging problems in the field of computational pathology. Currently, mitotic cell detection and counting are one of the strongest prognostic markers for breast cancer diagnosis. The clinical visual inspection on histology slides is tedious, error prone, and time consuming for the pathologist. Thus, automatic mitotic cell detection approaches are highly demanded in clinical practice. In this paper, we propose an end-to-end multi-task learning system for mitosis detection from pathological images which is named"MitosisNet". MitosisNet consist of segmentation, detection, and classification models where the segmentation, and detection models are used for mitosis reference region …

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The Picture Fuzzy Distance Measure In Controlling Network Power Consumption, Florentin Smarandache, Ngan Thi Roan, Salvador Coll Arnau, Marina Alonso Diaz, Juan Miguel Martinez Rubio, Pedro Lopez, Fran Andujar, Son Hoang Lee, Manh Van Vu Jan 2020

The Picture Fuzzy Distance Measure In Controlling Network Power Consumption, Florentin Smarandache, Ngan Thi Roan, Salvador Coll Arnau, Marina Alonso Diaz, Juan Miguel Martinez Rubio, Pedro Lopez, Fran Andujar, Son Hoang Lee, Manh Van Vu

Branch Mathematics and Statistics Faculty and Staff Publications

In order to solve the complex decision making problems, there are many approaches and systems based on fuzzy theory were proposed.

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Developing A Uas-Deployable Methane Sensor Using Low-Cost Modular Open-Source Components, Gavin Demali Jan 2020

Developing A Uas-Deployable Methane Sensor Using Low-Cost Modular Open-Source Components, Gavin Demali

Williams Honors College, Honors Research Projects

This project aimed to develop a methane sensor for deployment on an unmanned aerial system (UAS), or drone, platform. This design is centered around low cost, commercially available modular hardware components and open source software libraries. Once successfully developed, this system was deployed at the Bath Nature Preserve in Bath Township, Summit County Ohio in order to detect any potential on site fugitive methane emissions in the vicinity of the oil and gas infrastructure present. The deliverables of this project (i.e. the data collected at BNP) will be given to the land managers there to better inform future management and …

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Zips Racing Electric Can Communications, Andrew Jordan, Adam Long, Susanah Kowalewski, Rami Nehme Jan 2020

Zips Racing Electric Can Communications, Andrew Jordan, Adam Long, Susanah Kowalewski, Rami Nehme

Williams Honors College, Honors Research Projects

The CAN protocol has been a standard of electronic communication networks of automotive vehicles since the early 2000s due to its robust reliability in harsh environments. For the 2020 competition year, the Zips Racing Electric design team will be building an entirely new, fully-electric vehicle with CAN communication implemented rather than communicating via pure analog signals. Hardware and software can be utilized to read analog electrical signals from a source, such as accelerator and brake sensors, and encode them into a digital message that meets the CAN 2.0B communication protocol standard. Likewise, software can be used to extract data from …

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Kettlebell Ultra, Elissa Peters, Kathryn Wegman, Daniel Basch, Mason Pastorius Jan 2020

Kettlebell Ultra, Elissa Peters, Kathryn Wegman, Daniel Basch, Mason Pastorius

Williams Honors College, Honors Research Projects

This project will consist of an attachment to an average kettlebell that will track the number of repetitions that the user has performed. The device will send this data over Bluetooth to a smart phone application so the user can track their workout accurately.

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Vehicle Operator Attention Monitor, Matthew Krispinsky, Matt Marsek, Matthew Mayfield, Brian Call Jan 2020

Vehicle Operator Attention Monitor, Matthew Krispinsky, Matt Marsek, Matthew Mayfield, Brian Call

Williams Honors College, Honors Research Projects

Motor vehicle operators’ attention levels can be monitored to improve driver safety. By recording and analyzing the drivers eye gaze, hand position, vehicle speed and engine rpm the driver’s attention can be determined. A Raspberry Pi will be the main processing unit. Data will be pulled and analyzed from the OBD-II port on vehicle speed and engine rpm. The system will be powered from a 12V, 4A pin on the OBD-II port connected to the car battery. A webcam will be used to track the pupil location and determine when the driver is looking at the road. A battery powered …

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Design Of Subsurface Phased Array Antennas For Digital Agriculture Application, Abdul Salam Jan 2020

Design Of Subsurface Phased Array Antennas For Digital Agriculture Application, Abdul Salam

Faculty Publications

With the advancement in subsurface communications technology, an overarching solution to a underground phased array antenna design for digital agriculture requires interdisciplinary research involving topics ranging from insights on the constitutive parameters of the soil medium and impact of soil moisture on the array factor to antenna measurements and subsurface communication system design. In this paper, based on the analysis of underground radio wave propagation in subsurface radio channel, a phased array antenna design is presented that uses water content information and beam steering mechanisms to improve efficiency and communication range of wireless underground communications. It is shown the subsurface …

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Internet Of Things In Agricultural Innovation And Security, Abdul Salam Jan 2020

Internet Of Things In Agricultural Innovation And Security, Abdul Salam

Faculty Publications

The agricultural Internet of Things (Ag-IoT) paradigm has tremendous potential in transparent integration of underground soil sensing, farm machinery, and sensor-guided irrigation systems with the complex social network of growers, agronomists, crop consultants, and advisors. The aim of the IoT in agricultural innovation and security chapter is to present agricultural IoT research and paradigm to promote sustainable production of safe, healthy, and profitable crop and animal agricultural products. This chapter covers the IoT platform to test optimized management strategies, engage farmer and industry groups, and investigate new and traditional technology drivers that will enhance resilience of the farmers to the …

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Internet Of Things For Water Sustainability, Abdul Salam Jan 2020

Internet Of Things For Water Sustainability, Abdul Salam

Faculty Publications

The water is a finite resource. The issue of sustainable withdrawal of freshwater is a vital concern being faced by the community. There is a strong connection between the energy, food, and water which is referred to as water-food-energy nexus. The agriculture industry and municipalities are struggling to meet the demand of water supply. This situation is particularly exacerbated in the developing countries. The projected increase in world population requires more fresh water resources. New technologies are being developed to reduce water usage in the field of agriculture (e.g., sensor guided autonomous irrigation management systems). Agricultural water withdrawal is also …

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Internet Of Things For Sustainable Mining, Abdul Salam Jan 2020

Internet Of Things For Sustainable Mining, Abdul Salam

Faculty Publications

The sustainable mining Internet of Things deals with the applications of IoT technology to the coupled needs of sustainable recovery of metals and a healthy environment for a thriving planet. In this chapter, the IoT architecture and technology is presented to support development of a digital mining platform emphasizing the exploration of rock–fluid–environment interactions to develop extraction methods with maximum economic benefit, while maintaining and preserving both water quantity and quality, soil, and, ultimately, human health. New perspectives are provided for IoT applications in developing new mineral resources, improved management of tailings, monitoring and mitigating contamination from mining. Moreover, tools …

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Internet Of Things In Sustainable Energy Systems, Abdul Salam Jan 2020

Internet Of Things In Sustainable Energy Systems, Abdul Salam

Faculty Publications

Our planet has abundant renewable and conventional energy resources but technological capability and capacity gaps coupled with water-energy needs limit the benefits of these resources to citizens. Through IoT technology solutions and state-of-the-art IoT sensing and communications approaches, the sustainable energy-related research and innovation can bring a revolution in this area. Moreover, by the leveraging current infrastructure, including renewable energy technologies, microgrids, and power-to-gas (P2G) hydrogen systems, the Internet of Things in sustainable energy systems can address challenges in energy security to the community, with a minimal trade-off to environment and culture. In this chapter, the IoT in sustainable energy …

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Internet Of Things In Water Management And Treatment, Abdul Salam Jan 2020

Internet Of Things In Water Management And Treatment, Abdul Salam

Faculty Publications

The goal of the water security IoT chapter is to present a comprehensive and integrated IoT based approach to environmental quality and monitoring by generating new knowledge and innovative approaches that focus on sustainable resource management. Mainly, this chapter focuses on IoT applications in wastewater and stormwater, and the human and environmental consequences of water contaminants and their treatment. The IoT applications using sensors for sewer and stormwater monitoring across networked landscapes, water quality assessment, treatment, and sustainable management are introduced. The studies of rate limitations in biophysical and geochemical processes that support the ecosystem services related to water quality …

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Levitate, Stephen Hargreaves, Isaac Hammonds, Russel Pease, Joseph Morris Jan 2020

Levitate, Stephen Hargreaves, Isaac Hammonds, Russel Pease, Joseph Morris

Williams Honors College, Honors Research Projects

Levitate is designed to create a healthier work environment by providing a way of entertaining a worker while not distracting them. To fulfill this task, the device needs to be interesting and self-sufficient while not being overly flashy. To complete this task, Levitate is designed so that it is able to lift a platform from rest using magnetism and that will be able to stabilize itself using electromagnets. It initiates this process by lifting the permanent magnet using servo motors. Then, the device is able to achieve stability through the use of hall sensors feeding their results to the board …

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Digital, Automated Reactive Target System, Nicholas Haas, Saipranay Vellala, Trandon Ware, Thomas Martin Jan 2020

Digital, Automated Reactive Target System, Nicholas Haas, Saipranay Vellala, Trandon Ware, Thomas Martin

Williams Honors College, Honors Research Projects

In this era, technology is woven into almost every facet of our leisure activities. Although technology has innovated hobbies ranging from chess to soccer, the art of shooting has been neglected. Unnecessary insufficiency such as bullet ricochets off of mechanical steel targets, ineffective progress tracking, and general inaccessibility to outdoor training facilities are all improvable areas of this sport. The Dynamic Automated Reactive Target (D.A.R.T) System aims to fill some of these gaps and help modernize recreational marksmanship. Modeling the system after a dueling tree will optimize the use of the system and allow for different training models to challenge …

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Smart Collar, Gretchen T. Woodling, Sean Moran, Justen Bischoff, Jacob Sindelar Jan 2020

Smart Collar, Gretchen T. Woodling, Sean Moran, Justen Bischoff, Jacob Sindelar

Williams Honors College, Honors Research Projects

The Smart Collar is a universal pet tracker, designed to be small and exceedingly comfortable for any pet to wear. GPS technology is used to locate the device, allowing the user to track their pet, via a smart phone application. This application can be used to program the device, view maps of their pet’s location and history of travel. Operating primarily on Long Range Wide Area Network (LoRaWAN) for data transfer, the device consumes very little power, allowing for several days of run-time per charge of the battery. Boasting no monthly service fees, The Smart Collar provides pet owner’s an …

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