89 research outputs found
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
Efficient information distribution in the Internet of Medical Things (IoMT)
Towards the world of Internet of Things, people utilize knowledge from sensor
streams in various kinds of smart applications including, but not limited to smart
medical information systems. The number of sensed devices is rapidly increasing
along with the amount of sensing data. Consequently, the bottleneck problem
at the local gateway has become a huge concern given the critical loss and delay
intolerant nature of medical data. Orthogonally to the existing solutions, we
propose sensor data prioritization mechanism to enhance the information quality
while utilizing resources using Value of Information (VoI) at the application
level. Our approach adopts signal processing techniques and information theory
related concepts to assess the VoI. We introduce basic yet convenient ways to
enhance the efficiency of medical information systems, not only when considering
the resource consumption, but also when performing updates, by selecting
appropriate delay for wearable sensors to send data at optimal VoI. Our analysis
shows some interesting results about the correlation and dependency of different
sensor signals, that we use for the value assesment. This preliminary analysis
could be an initiative for further investigation of VoI in medical data transmission
using more advanced methods.Towards the world of Internet of Things, people utilize knowledge from sensor
streams in various kinds of smart applications including, but not limited to smart
medical information systems. The number of sensed devices is rapidly increasing
along with the amount of sensing data. Consequently, the bottleneck problem
at the local gateway has become a huge concern given the critical loss and delay
intolerant nature of medical data. Orthogonally to the existing solutions, we
propose sensor data prioritization mechanism to enhance the information quality
while utilizing resources using Value of Information (VoI) at the application
level. Our approach adopts signal processing techniques and information theory
related concepts to assess the VoI. We introduce basic yet convenient ways to
enhance the efficiency of medical information systems, not only when considering
the resource consumption, but also when performing updates, by selecting
appropriate delay for wearable sensors to send data at optimal VoI. Our analysis
shows some interesting results about the correlation and dependency of different
sensor signals, that we use for the value assesment. This preliminary analysis
could be an initiative for further investigation of VoI in medical data transmission
using more advanced methods
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