2020
DOI: 10.48550/arxiv.2001.00090
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Resilient Cyberphysical Systems and their Application Drivers: A Technology Roadmap

Somali Chaterji,
Parinaz Naghizadeh,
Muhammad Ashraful Alam
et al.

Abstract: Cyberphysical systems (CPS) are ubiquitous in our personal and professional lives, and they promise to dramatically improve micro-communities (e.g., urban farms, hospitals), macro-communities (e.g., cities and metropolises), urban structures (e.g., smart homes and cars), and living structures (e.g., human bodies, synthetic genomes). The question that we address in this article pertains to designing these CPS systems to be resilient-from-the-ground-up, and in "learning" iterations, resilientby-reaction. An opti… Show more

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Cited by 3 publications
(4 citation statements)
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References 92 publications
(95 reference statements)
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“…Therefore, we select these two applications as representative workloads for computelight vs. compute-intensive IoT applications. IoT devices are used for simple data acquisition in many scenarios, like in farms [11,21] and for self-driving cars [9,12]. Since the volume of data acquired through these sensors is high, it is often run through an outlier detection program to ensure proper analysis of data and to discover faulty sensors.…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, we select these two applications as representative workloads for computelight vs. compute-intensive IoT applications. IoT devices are used for simple data acquisition in many scenarios, like in farms [11,21] and for self-driving cars [9,12]. Since the volume of data acquired through these sensors is high, it is often run through an outlier detection program to ensure proper analysis of data and to discover faulty sensors.…”
Section: Introductionmentioning
confidence: 99%
“…Traditionally, it has been challenging to consistently monitor large farmlands due to the lack of automation and inefficient labor. Recent agricultural industries have been adopting automation technologies that can monitor the environment and optimize farming [1]- [4]. Some analytics can also be run on the back-end cloud computing resource and derive actionable knowledge from the raw data, such as, how to fertilize specific parts of the farm in a localized manner.…”
mentioning
confidence: 99%
“…2))) * rad_to_degree_coeff) -imu_offset [1]; accel_angles [2] = (atan2(accel_raw [2], sqrt(pow(accel_raw[0], 2) + pow(accel_raw [1],…”
Section: Resultsmentioning
confidence: 99%
“…The steady advancement in sensing, actuation, and control system computing technologies has led to the development of complex systems, including smartphones, autonomous vehicles, smart grids, automated buildings, and smart cities [1]. The common characteristic of these systems is the tight coupling of hardware and software capabilities and constraints as well as the combination of heterogeneous components.…”
Section: Chapter 1: Introductionmentioning
confidence: 99%