2017
DOI: 10.1007/s13369-017-2893-4
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A Simulation Study of Adaptive Force Controller for Medical Robotic Liver Ultrasound Guidance

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Cited by 23 publications
(10 citation statements)
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“…This study presented a new mobile application; namely GASDUINO to allow the users to measure and classify the level of the air pollution using the Internet of Things (IoT) successfully. The future work of this project will include the following prospects: 1) Create a network of wireless gas sensors to cover more than one place simultaneously for monitoring the AQI during 24 hours; 2) Improve the developed mobile application to display the percentage of each gas emission individually in the air with the overall PPM values; 3) Using artificial intelligence models like neural networks [18] and fuzzy systems [19] for predicting the air quality levels per time, e.g. weeks or months; and 4) Applying the developed GASDUINO system in the industrial areas of Shaqra city, Saudi Arabia.…”
Section: Discussionmentioning
confidence: 99%
“…This study presented a new mobile application; namely GASDUINO to allow the users to measure and classify the level of the air pollution using the Internet of Things (IoT) successfully. The future work of this project will include the following prospects: 1) Create a network of wireless gas sensors to cover more than one place simultaneously for monitoring the AQI during 24 hours; 2) Improve the developed mobile application to display the percentage of each gas emission individually in the air with the overall PPM values; 3) Using artificial intelligence models like neural networks [18] and fuzzy systems [19] for predicting the air quality levels per time, e.g. weeks or months; and 4) Applying the developed GASDUINO system in the industrial areas of Shaqra city, Saudi Arabia.…”
Section: Discussionmentioning
confidence: 99%
“…As mentioned above, three modes are concluded as autonomous, teleoperation and human‐robot cooperative control. Furthermore, various control methods such as the three‐channel environment force compensation (EFC) control [69], PD control [10], adaptive control [70], neural network (NN) control [71] and fuzzy control [72] are taken to solve US guidance with uncertain environmental forces [69], and varying time delays.…”
Section: Challenges and Key Technologiesmentioning
confidence: 99%
“…On the other side, the technology of wireless sensor networks (WSN) has been applied to the agriculture sector to offer new trends like Precision Agriculture (PA) [10]. Emerging the WSN with advanced knowledge-based fuzzy controller [11] were proposed to automate the water levels of irrigation system [12]. Moreover, using embedded and electronic boards such as STC89C52 MCU (Micro Control Unit) was proposed to provide a controller for smart irrigation system [13].…”
Section: Introductionmentioning
confidence: 99%