Destination Area: Intelligent Infrastructure for Human-Centered Communities (IIHCC)
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IIHCC focuses its attention on the ways that people interact with one another and with their environment. Interest areas in this DA include smart, healthy, and sustainable cities and communities; transportation systems; human safety, health, and wellness; integrated energy systems; network science and engineering; public policy; and cyber-physical systems. The initial focus for IIHCC will be on four themes:
Ubiquitous Mobility: The location-agnostic promise of new communication and information technologies
Automated Vehicle Systems: vehicles that can transit safely and efficiently through our communities independent of a human operator
Smart Design and Construction: an intelligent, integrated, adaptable, responsive, and sustainable human-centric built environment
Energy: the underlying innovations that will be required in the production, distribution, and consumption of energy to realize such a system
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Browsing Destination Area: Intelligent Infrastructure for Human-Centered Communities (IIHCC) by Department "Electrical and Computer Engineering"
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- 3D printed graphene-based self-powered strain sensors for smart tires in autonomous vehiclesMaurya, Deepam; Khaleghian, Seyedmeysam; Sriramdas, Rammohan; Kumar, Prashant; Kishore, Ravi Anant; Kang, Min-Gyu; Kumar, Vireshwar; Song, Hyun-Cheol; Lee, Seul-Yi; Yan, Yongke; Park, Jung-Min (Jerry); Taheri, Saied; Priya, Shashank (2020-10-26)The transition of autonomous vehicles into fleets requires an advanced control system design that relies on continuous feedback from the tires. Smart tires enable continuous monitoring of dynamic parameters by combining strain sensing with traditional tire functions. Here, we provide breakthrough in this direction by demonstrating tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis. Ink of graphene based material was designed to directly print strain sensor for measuring tire-road interactions under varying driving speeds, normal load, and tire pressure. A secure wireless data transfer hardware powered by a piezoelectric patch is implemented to demonstrate self-powered sensing and wireless communication capability. Combined, this study significantly advances the design and fabrication of cost-effective smart tires by demonstrating practical self-powered wireless strain sensing capability. Designing efficient sensors for smart tires for autonomous vehicles remains a challenge. Here, the authors present a tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis.
- CU-BEMS, smart building electricity consumption and indoor environmental sensor datasetsPipattanasomporn, Manisa; Chitalia, Gopal; Songsiri, Jitkomut; Aswakul, Chaodit; Pora, Wanchalerm; Suwankawin, Surapong; Audomvongseree, Kulyos; Hoonchareon, Naebboon (2020-07-20)This paper describes the release of the detailed building operation data, including electricity consumption and indoor environmental measurements, of the seven-story 11,700-m(2) office building located in Bangkok, Thailand. The electricity consumption data (kW) are that of individual air conditioning units, lighting, and plug loads in each of the 33 zones of the building. The indoor environmental sensor data comprise temperature (degrees C), relative humidity (%), and ambient light (lux) measurements of the same zones. The entire datasets are available at one-minute intervals for the period of 18 months from July 1, 2018, to December 31, 2019. Such datasets can be used to support a wide range of applications, such as zone-level, floor-level, and building-level load forecasting, indoor thermal model development, validation of building simulation models, development of demand response algorithms by load type, anomaly detection methods, and reinforcement learning algorithms for control of multiple AC units.
- Environmental Information Improves Robotic Search PerformanceYetkin, Harun; Lutz, Collin C.; Stilwell, Daniel J. (Virginia Tech, 2016)We address the problem where a mobile search agent seeks to find an unknown number of stationary objects distributed in a bounded search domain, and the search mission is subject to time/distance constraint. Our work accounts for false positives, false negatives and environmental uncertainty. We consider the case that the performance of a search sensor is dependent on the environment (e.g., clutter density), and therefore sensor performance is better in some locations than in others. For applications where environmental information can be acquired, we derive a decision-theoretic cost function to compute the locations where the environmental information should be acquired. We address the cases where environmental characterization is performed either by a separate vehicle or by the same vehicle that performs the search task.
- A Framework for Occupancy Tracking in a Building via Structural Dynamics Sensing of Footstep VibrationsPoston, Jeffrey D.; Buehrer, R. Michael; Tarazaga, Pablo Alberto (Frontiers, 2017-11-06)Counting the number of occupants in building areas over time—occupancy tracking— provides valuable information for responding to emergencies, optimizing thermal conditions or managing personnel. This capability is distinct from tracking individual building occupants as they move within a building, has lower complexity than conventional tracking algorithms require, and avoids privacy concerns that tracking individuals may pose. The approach proposed here is a novel combination of data analytics applied to measurements from a building’s structural dynamics sensors (e.g., accelerometers or geophones). Specifically, measurements of footstep-generated structural waves provide evidence of occupancy in a building area. These footstep vibrations can be distinguished from other vibrations, and, once identified, the footsteps can be located. These locations, in turn, form the starting point of estimating occupancy in an area. In order to provide a meaningful occupancy count, however, it is first necessary to associate discrete footsteps with individuals. The proposed framework incorporates a tractable algorithm for this association task. The proposed algorithms operate online, updating occupancy count over time as new footsteps are detected. Experiments with measurements from a public building illustrate the operation of the proposed framework. This approach offers an advantage over others based on conventional technologies by avoiding the cost of a separate sensor system devoted to occupancy tracking.
- A Fully-Distributed Heuristic Algorithm for Control of Autonomous Vehicle Movements at Isolated IntersectionsHassan, Abdallah A.; Rakha, Hesham A. (Elsevier, 2014)Optimizing autonomous vehicle movements through roadway intersections is a challenging problem. It has been demonstrated in the literature that traditional traffic control, such as traffic signal and stop sign control are not optimal especially for heavy traffic demand levels. Alternatively, centralized autonomous vehicle control strategies are costly and not scalable given that the ability of a central controller to track and schedule the movement of hundreds of vehicles in real-time is questionable. Consequently, in this paper a fully distributed algorithm is proposed where vehicles in the vicinity of an intersection continuously cooperate with each other to develop a schedule that allows them to safely proceed through the intersection while incurring minimum delay. Unlike other distributed approaches described in the literature, the wireless communication constraints are considered in the design of the control algorithm. Specifically, the proposed algorithm requires vehicles heading to an intersection to communicate only with neighboring vehicles, while the lead vehicles on each approach lane share information to develop a complete intersection utilization schedule. The scheduling rotates between vehicles to identify higher traffic volumes and favor vehicles coming from heavier lanes to minimize the overall intersection delay. The simulated experiments show significant reductions in the average delay using the proposed approach compared to other methods reported in the literature and reduction in the maximum delay experienced by a vehicle especially in cases of heavy traffic demand levels.
- An Open Source Modeling Framework for Interdependent Energy-Transportation-Communication Infrastructure in Smart and Connected CommunitiesLu, Xing; Hinkelman, Kathryn; Fu, Yangyang; Wang, Jing; Zuo, Wangda; Zhang, Qianqian; Saad, Walid (IEEE, 2019)Infrastructure in future smart and connected communities is envisioned as an aggregate of public services, including energy, transportation, and communication systems, all intertwined with each other. The intrinsic interdependency among these systems may exert the underlying influence on both design and operation of the heterogeneous infrastructures. However, few prior studies have tapped into the interdependency among these systems in order to quantify their potential impacts during standard operation. In response to this, this paper proposes an open-source, flexible, integrated modeling framework suitable for designing coupled energy, transportation, and communication systems and for assessing the impact of their interdependencies. First, a novel multi-level, multi-layer, multi-agent approach is proposed to enable flexible modeling of the interconnected systems. Then, for the framework's proof of concept, preliminary component and system-level models for different systems are designed and implemented using Modelica, an equation-based object-oriented modeling language. Finally, three case studies of gradually increasing complexity are presented (energy, energy + transportation, and energy + transportation + communication) to evaluate the interdependencies among the three systems. Quantitative analyses show that the deviation of the average velocity on the road can be 10.5% and the deviation of the power drawn from the grid can be 7% with or without considering the transportation and communication system at the peak commute time, indicating the presence of notable interdependencies. The proposed modeling framework also has the potential to be further extended for various modeling purposes and use cases, such as dynamic modeling and optimization, resilience analysis, and integrated decision making in future connected communities.
- Optimize the Communication Cost of 5G Internet of Vehicles through Coherent Beamforming TechnologyWu, Lan; Xu, Juan; Shi, Lei; Shi, Yi; Zhou, Wenwen (Hindawi, 2021-05-17)Edge computing, which sinks a large number of complex calculations into edge servers, can effectively meet the requirement of low latency and bandwidth efficiency and can be conducive to the development of the Internet of Vehicles (IoV). However, a large number of edge servers mean a big cost, especially for the 5G scenario in IoV, because of the small coverage of 5G base stations. Fortunately, coherent beamforming (CB) technology enables fast and long-distance transmission, which gives us a possibility to reduce the number of 5G base stations without losing the whole network performance. In this paper, we try to adopt the CB technology on the IoV 5G scenario. We suppose we can arrange roadside nodes for helping transferring tasks of vehicles to the base station based on the CB technology. We first give the mathematical model and prove that it is a NP-hard model that cannot be solved directly. Therefore, we design a heuristic algorithm for an Iterative Coherent Beamforming Node Design (ICBND) algorithm to obtain the approximate optimal solution. Simulation results show that this algorithm can greatly reduce the cost of communication network infrastructure.
- Riverine AutonomyStilwell, Daniel J. (Defense Technical Information Center, 2013-09-30)The principal goal of this project is to develop the technology and algorithms that will enable an unmanned surface vehicle (USV) to operate fast and autonomously in unknown riverine environments, including tropical rivers. Robust autonomy requires that the USV senses the surface and subsurface environments, discriminates waterways that are navigable from those that are not, identifies stationary and moving obstacles, including other vessels, and then optimally plans and re-plans a route in realtime. Since speed is a vessel’s principal defense, all of these tasks must be done as efficiently as possible to ensure successful operation at the greatest possible speed. This project is tightly coordinated with collaborators at the Naval Postgraduate School (NPS) whose work is conducted under a related project.
- Sensing and Autonomy for Riverine VesselsStilwell, Daniel J.; Woolsey, Craig A. (Defense Technical Information Center, 2012)The principal goal of this project is to develop the technology and algorithms that will enable an unmanned surface vehicle (USV) to operate fast and autonomously in unknown riverine environments, including tropical rivers. Robust autonomy requires that the USV senses the surface and subsurface environments, discriminates waterways that are navigable from those that are not, identifies stationary and moving obstacles, including other vessels, and then optimally plans and re-plans a route in realtime. Since speed is a vessel’s principal defense, all of these tasks must be done as efficiently as possible to ensure successful operation at the greatest possible speed. This project is tightly coordinated with collaborators at the Naval Postgraduate School (NPS) whose work is conducted under a related project.