Distributed Sensor Networks as Sensate Skin
نویسندگان
چکیده
We have designed and constructed a hardware test bed to explore the application of a dense, multi-modal, peerto-peer sensor network as an electronic ”skin”; a sensate lining that covers an object to sense, process, and coarsely classify local stimuli. Resulting parameters can be routed between nodes (which we term skin ”patches”) neighbor-to-neighbor to a portal for external analysis and/or produce a local response with a set of actuators built into each patch. The resulting device is a roughly 33-cm diameter sphere tiled with such patches. Each patch sports an array of vibration-sensitive whiskers, sensors for local pressure, light, sound, and temperature, as well as actuators for a full range of colors, vibrations, and sound. All these sensors and actuators fall under the control of a dense, distributed sensor network, as each patch is connected to its neighbors. Geometrically, this device, termed ”Tribble”, resembles a soccer ball, where each face is a single patch of skin.
منابع مشابه
Sensate media — multimodal electronic skins as dense sensor networks
In this paper, we introduce the concept of building electronic sensate skins as extremely dense, multimodal, systolic sensor networks. In this fashion, the copious signals produced by the skin’s receptors are reduced by the network itself, and only high-level features are routed out peer-to-peer, avoiding complex wiring requirements while promising to enable scalability across large areas. Our ...
متن کاملDynamic Obstacle Avoidance by Distributed Algorithm based on Reinforcement Learning (RESEARCH NOTE)
In this paper we focus on the application of reinforcement learning to obstacle avoidance in dynamic Environments in wireless sensor networks. A distributed algorithm based on reinforcement learning is developed for sensor networks to guide mobile robot through the dynamic obstacles. The sensor network models the danger of the area under coverage as obstacles, and has the property of adoption o...
متن کاملMulticast Routing in Wireless Sensor Networks: A Distributed Reinforcement Learning Approach
Wireless Sensor Networks (WSNs) are consist of independent distributed sensors with storing, processing, sensing and communication capabilities to monitor physical or environmental conditions. There are number of challenges in WSNs because of limitation of battery power, communications, computation and storage space. In the recent years, computational intelligence approaches such as evolutionar...
متن کاملDesign and evaluation of two distributed methods for sensors placement in Wireless Sensor Networks
Adequate coverage is one of the main problems for distributed wireless sensor networks and The effectiveness of that highly depends on the sensor deployment scheme. Given a finite number of sensors, optimizing the sensor deployment will provide sufficient sensor coverage and save power of sensors for movement to target location to adequate coverage. In this paper, we apply fuzzy logic system to...
متن کاملOutlier Detection in Wireless Sensor Networks Using Distributed Principal Component Analysis
Detecting anomalies is an important challenge for intrusion detection and fault diagnosis in wireless sensor networks (WSNs). To address the problem of outlier detection in wireless sensor networks, in this paper we present a PCA-based centralized approach and a DPCA-based distributed energy-efficient approach for detecting outliers in sensed data in a WSN. The outliers in sensed data can be ca...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2003