Search results for "low power"
showing 9 items of 9 documents
eISP, une architecture de calcul programmable pour l'amélioration d'images sur téléphone portable.
2009
4 pages; Today's smart phones, with their embedded high-resolution video sensors, require computing capacities that are too high to easily meet stringent silicon area and power consumption requirements (some one and a half square millimeters and half a watt) especially when programmable components are used. To develop such capacities, integrators still rely on dedicated low resolution video processing components, whose drawback is low flexibility. With this in mind, our paper presents eISP {--} a new, fully programmable Embedded Image Signal Processor architecture, now validated in {TSMC~65nm} technology to achieve a capacity of {16.8~GOPs} at {233~MHz}, for {1.5~mm$^2$} of silicon area and…
An Energy-Autonomous Wireless Sensor with Simultaneous Energy Harvesting and Ambient Light Sensing
2021
Wireless sensor nodes (WSNs) are generally powered by batteries, which results in a substantial limitation to the places where the nodes can be installed, to the maximum number of deployable devices, and to the node lifetime. To meet the demand for Internet-of-Things (IoT) applications that require a large number of maintenance-free, low cost, wireless sensor nodes, this paper proposes a wireless sensor platform with a single photovoltaic transducer that performs the dual role of harvesting energy and sensing ambient light. This dual use allows even smaller and cheaper nodes that do not require any form of supporting external power, with a reduced component count. The device implements off-…
eISP: a Programmable Processing Architecture for Smart Phone Image Enhancement
2009
4 pages; Today's smart phones, with their embedded high-resolution video sensors, require computing capacities that are too high to easily meet stringent silicon area and power consumption requirements (some one and a half square millimeters and half a watt) especially when programmable components are used. To develop such capacities, integrators still rely on dedicated low resolution video processing components, whose drawback is low flexibility. With this in mind, our paper presents eISP {--} a new, fully programmable Embedded Image Signal Processor architecture, now validated in {TSMC 65nm} technology to achieve a capacity of {16.8 GOPs} at {233 MHz}, for {1.5 mm$^2$} of silicon area and…
AI for Resource Allocation and Resource Allocation for AI: a two-fold paradigm at the network edge
2022
5G-and-beyond and Internet of Things (IoT) technologies are pushing a shift from the classic cloud-centric view of the network to a new edge-centric vision. In such a perspective, the computation, communication and storage resources are moved closer to the user, to the benefit of network responsiveness/latency, and of an improved context-awareness, that is, the ability to tailor the network services to the live user's experience. However, these improvements do not come for free: edge networks are highly constrained, and do not match the resource abundance of their cloud counterparts. In such a perspective, the proper management of the few available resources is of crucial importance to impr…
An energy analysis of IEEE 802.15.6 scheduled access modes
2010
Body Area Networks (BANs) are an emerging area of wireless personal communications. The IEEE 802.15.6 working group aims to develop a communications standard optimised for low power devices operating on, in or around the human body. IEEE 802.15.6 specifically targets low power medical application areas. The IEEE 802.15.6 draft defines two main channel access modes; contention based and contention free. This paper examines the energy lifetime performance of contention free access and in particular of periodic scheduled allocations. This paper presents an overview of the IEEE 802.15.6 and an analytical model for estimating the device lifetime. The analysis determines the maximum device lifeti…
Embedding Monitoring Systems for Cured-In-Place Pipes
2017
This paper proposes a non-intrusive electrical measurement system for monitoring some relevant parameters in pipeline systems. Temperature and flow-rate are monitored, using MEMS sensors. The flow-rate is evaluated by measuring pipe vibration, with a 3 axis accelerometer, induced by turbulence when fluid flows within the tube. The sensors are embedded, during the curing process of the cured-in-place pipes, in the pipes wall making the system suitable to be installed in renewed or new pipeline. The first experimental results show that it may be possible to obtain, at low-cost, a fully monitored distribution network.
A low power and high resolution data logger for submarine seismic monitoring
2010
The design, implementation and characterization of a digital waveform recorder for ocean bottom seismic monitoring is here reported. The system is capable of synchronously acquiring, and logging on a flash memory bank, four high resolution signals. Thanks to a very careful design of the system architecture and by using robust digital signal processing techniques, two main conflicting issues have been addressed: a high dynamic range, better than 120 dB, usually obtained with high energy demanding converters, and a power consumption as low as 250 mW, hence allowing to easily increase the time of a continuous submarine monitoring session up to 3 months.
Performance of LoRa for Bike-Sharing Systems
2019
Today bike sharing systems are becoming popular in many cities as short-distance transit vehicles. More than 18 million bicycles are available worldwide for public use and one of the main problems that afflicts such sharing systems is the loss of bikes, which can be stolen or simply left in unknown locations. Thus, many bikes are docked or tracked using GPS and costly cellular connections. In this paper, we consider the emerging Long Range (LoRa) technology for use in bike sharing systems. LoRa exploits free ISM bands and has been conceived for low power and low data rate applications. Additionally, LoRa is characterized by large cells and heterogeneous application domains, which may lead t…
PNeuro: A scalable energy-efficient programmable hardware accelerator for neural networks
2018
Proceedings of a meeting held 19-23 March 2018, Dresden, Germany; International audience; Artificial intelligence and especially Machine Learning recently gained a lot of interest from the industry. Indeed, new generation of neural networks built with a large number of successive computing layers enables a large amount of new applications and services implemented from smart sensors to data centers. These Deep Neural Networks (DNN) can interpret signals to recognize objects or situations to drive decision processes. However, their integration into embedded systems remains challenging due to their high computing needs. This paper presents PNeuro, a scalable energy-efficient hardware accelerat…