Current Issue : July - September Volume : 2016 Issue Number : 3 Articles : 4 Articles
In Wireless Sensor Networks (WSNs), Context Awareness is typically realized through Context Aware Systems (CASs). Although\nalmost each CAS follows sense-decide-adapt cycle, the notion of context is hardwired into the applications; that is, when an event\nis triggered, the sense-decide-actuate cycle runs and performs required actuation. In situations, for instance, whenever the same\nevent is triggered, the cycle produces the same actuation throughmechanical use of the same resources, posing the same processing\nand time. In this paper, we propose CRAM, a context added system in which actuations once performed by the system help it to\ninternally evolve by serving as new contexts. As the system is exposed to more situations overtime, its context repository is enriched\nthrough such retrospective contexts, gradually letting it perform internal actuation through improved introspective contexts. This\ninternal actuation leads the system towards the evolution of intelligent processing by reducing the independent function of decision\nin sense-decide-actuate cycle and merging it with new context. Finally, the system reaches a juncture where recurrence of each event\nproves to be a stimulus for the system to respond impulsively, through priming memory of introspective contexts, to achieve an\nimitation of learned reflex action resulting into reduced time and energy expenditure....
Google Glass is a recently designed wearable device capable of displaying information in a smartphone-like hands-free format by wireless communication. The Glass also provides convenient control over remote devices, primarily enabled by voice recognition commands. These unique features of the Google Glass make it useful for medical and biomedical applications where hands-free experiences are strongly preferred. Here, we report for the first time, an integral set of hardware, firmware, software, and Glassware that enabled wireless transmission of sensor data onto the Google Glass for on-demand data visualization and real-time analysis. Additionally, the platform allowed the user to control outputs entered through the Glass, therefore achieving bi-directional Glass-device interfacing. Using this versatile platform, we demonstrated its capability in monitoring physical and physiological parameters such as temperature, pH, and morphology of liver- and heart-on-chips. Furthermore, we showed the capability to remotely introduce pharmaceutical compounds into a microfluidic human primary liver bioreactor at desired time points while monitoring their effects through the Glass. We believe that such an innovative platform, along with its concept, has set up a premise in wearable monitoring and controlling technology for a wide variety of applications in biomedicine....
This paper presents the development of a newly designed wireless piezoelectric (PZT) sensor platform for distributed large-scale\nstructure health monitoring, where real-time data acquisition with high sampling rate up to 12.5 Msps (sample per second) and\ndistributed lamb-wave data processing are implemented. In the proposed wireless PZT network, a set of PZT transducers are\ndeployed at the surface of the structure, a lamb-wave is excited, and its propagation characteristics within the structure are inspected\nto identify damages. The developed wireless node platform features a digital signal processor (DSP) of TMS320F28335 and an\nimproved IEEE 802.15.4 wireless data transducer RF233 with up to 2Mbps data rate. Each node supports up to 8 PZT transducers,\none of whichworks as the actuator generating the lamb-wave at an arbitrary frequency,while the responding vibrations at other PZT\nsensors are sensed simultaneously. In addition to hardware, embedded signal processing and distributed data processing algorithm\nare designed as the intelligent ââ?¬Å?brainââ?¬Â of the proposed wireless monitoring network to extract features of the PZT signals, so that\nthe data transmitted over the wireless link can be reduced significantly....
The excellent compliance and large range of motion of soft actuators controlled by fluid\npressure has lead to strong interest in applying devices of this type for biomimetic and human-robot\ninteraction applications. However, in contrast to soft actuators fabricated from stretchable silicone\nmaterials, conventional technologies for position sensing are typically rigid or bulky and are not ideal\nfor integration into soft robotic devices. Therefore, in order to facilitate the use of soft pneumatic\nactuators in applications where position sensing or closed loop control is required, a soft pneumatic\nbending actuator with an integrated carbon nanotube position sensor has been developed. The\nintegrated carbon nanotube position sensor presented in this work is flexible and well suited to\nmeasuring the large displacements frequently encountered in soft robotics. The sensor is produced by\na simple soft lithography process during the fabrication of the soft pneumatic actuator, with a greater\nthan 30% resistance change between the relaxed state and the maximum displacement position. It is\nanticipated that integrated resistive position sensors using a similar design will be useful in a wide\nrange of soft robotic systems....
Loading....