A Bio-Inspired Vision Sensor With Dual Operation and Readout Modes

This paper presents a novel event-based vision sensor with two operation modes: intensity mode and spatial contrast detection. They can be combined with two different readout approaches: pulse density modulation and time-to-first spike. The sensor is conceived to be a node of an smart camera network made up of several independent an autonomous nodes that send information to a central one. The user can toggle the operation and the readout modes with two control bits. The sensor has low latency (below 1 ms under average illumination conditions), low power consumption (19 mA), and reduced data flow, when detecting spatial contrast. A new approach to compute the spatial contrast based on inter-pixel event communication less prone to mismatch effects than diffusive networks is proposed. The sensor was fabricated in the standard AMS4M2P 0.35-um process. A detailed system-level description and experimental results are provided.Office of Naval Research (USA) N00014-14-1-0355Ministerio de Economía y Competitividad TEC2012- 38921-C02-02, P12-TIC-2338, IPT-2011-1625-43000

Sun Sensor Based on a Luminance Spiking Pixel Array

We present a novel sun sensor concept. It is the very first sun sensor built with an address event representation spiking pixel matrix. Its pixels spike with a frequency proportional to illumination. It offers remarkable advantages over conventional digital sun sensors based on active pixel sensor (APS) pixels. Its output data flow is quite reduced. It is possible to resolve the sun position just receiving one single event operating in time-to-first-spike mode. It operates with a latency in the order of milliseconds. It has higher dynamic range than APS image sensors (higher than 100 dB). A custom algorithm to compute the centroid of the illuminated pixels is presented. Experimental results are provided.Universidad de Cádiz PR2016-072Ministerio de Economía y Competitividad TEC2015-66878-C3-1-RJunta de Andalucía TIC 2012- 2338Office of Naval Research (USA) N00014141035

Homogeneous Spiking Neuromorphic System for Real-World Pattern Recognition

A neuromorphic chip that combines CMOS analog spiking neurons and memristive synapses offers a promising solution to brain-inspired computing, as it can provide massive neural network parallelism and density. Previous hybrid analog CMOS-memristor approaches required extensive CMOS circuitry for training, and thus eliminated most of the density advantages gained by the adoption of memristor synapses. Further, they used different waveforms for pre and post-synaptic spikes that added undesirable circuit overhead. Here we describe a hardware architecture that can feature a large number of memristor synapses to learn real-world patterns. We present a versatile CMOS neuron that combines integrate-and-fire behavior, drives passive memristors and implements competitive learning in a compact circuit module, and enables in-situ plasticity in the memristor synapses. We demonstrate handwritten-digits recognition using the proposed architecture using transistor-level circuit simulations. As the described neuromorphic architecture is homogeneous, it realizes a fundamental building block for large-scale energy-efficient brain-inspired silicon chips that could lead to next-generation cognitive computing.Comment: This is a preprint of an article accepted for publication in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol 5, no. 2, June 201

A micropower centroiding vision processor

Published versio

A sun sensor implemented with an asynchronous luminance vision sensor

A sun sensor implemented with a spiking pixel matrix is reported. It is the very first one based on an asynchronous event-based pixel array. A paradigm associated to classic digital sun sensors is solved with this approach. Only pixels illuminated by the sun light are readout. Hence, the output data flow is quite reduced. The computational load to resolve the sun position is quite low, comparing to prior sensors. Sensor's latency is in the order of milliseconds. The advantages over implementations with APS pixels are more reduced data flow, less latency, and higher dynamic range.Universidad de Cádiz PR2016-072Ministerio de Economía y Competitividad TEC2015-66878- C3-1-RJunta de Andalucía TIC 2012-2338Office of Naval Research (USA) N00014141035

An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

Near-sensor data analytics is a promising direction for IoT endpoints, as it minimizes energy spent on communication and reduces network load - but it also poses security concerns, as valuable data is stored or sent over the network at various stages of the analytics pipeline. Using encryption to protect sensitive data at the boundary of the on-chip analytics engine is a way to address data security issues. To cope with the combined workload of analytics and encryption in a tight power envelope, we propose Fulmine, a System-on-Chip based on a tightly-coupled multi-core cluster augmented with specialized blocks for compute-intensive data processing and encryption functions, supporting software programmability for regular computing tasks. The Fulmine SoC, fabricated in 65nm technology, consumes less than 20mW on average at 0.8V achieving an efficiency of up to 70pJ/B in encryption, 50pJ/px in convolution, or up to 25MIPS/mW in software. As a strong argument for real-life flexible application of our platform, we show experimental results for three secure analytics use cases: secure autonomous aerial surveillance with a state-of-the-art deep CNN consuming 3.16pJ per equivalent RISC op; local CNN-based face detection with secured remote recognition in 5.74pJ/op; and seizure detection with encrypted data collection from EEG within 12.7pJ/op.Comment: 15 pages, 12 figures, accepted for publication to the IEEE Transactions on Circuits and Systems - I: Regular Paper

A sub-mW IoT-endnode for always-on visual monitoring and smart triggering

This work presents a fully-programmable Internet of Things (IoT) visual sensing node that targets sub-mW power consumption in always-on monitoring scenarios. The system features a spatial-contrast $128\mathrm{x}64$ binary pixel imager with focal-plane processing. The sensor, when working at its lowest power mode ($10\mu W$ at 10 fps), provides as output the number of changed pixels. Based on this information, a dedicated camera interface, implemented on a low-power FPGA, wakes up an ultra-low-power parallel processing unit to extract context-aware visual information. We evaluate the smart sensor on three always-on visual triggering application scenarios. Triggering accuracy comparable to RGB image sensors is achieved at nominal lighting conditions, while consuming an average power between $193\mu W$ and $277\mu W$, depending on context activity. The digital sub-system is extremely flexible, thanks to a fully-programmable digital signal processing engine, but still achieves 19x lower power consumption compared to MCU-based cameras with significantly lower on-board computing capabilities.Comment: 11 pages, 9 figures, submitteted to IEEE IoT Journa

Influence of microphone housing on the directional response of piezoelectric mems microphones inspired by Ormia ochracea

The influence of custom microphone housings on the acoustic directionality and frequency response of a multiband bio-inspired MEMS microphone is presented. The 3.2 mm by 1.7 mm piezoelectric MEMS microphone, fabricated by a cost-effective multi-user process, has four frequency bands of operation below 10 kHz, with a desired first-order directionality for all four bands. 7×7×2.5 mm3 3-D-printed bespoke housings with varying acoustic access to the backside of the microphone membrane are investigated through simulation and experiment with respect to their influence on the directionality and frequency response to sound stimulus. Results show a clear link between directionality and acoustic access to the back cavity of the microphone. Furthermore, there was a change in direction of the first-order directionality with reduced height in this back cavity acoustic access. The required configuration for creating an identical directionality for all four frequency bands is investigated along with the influence of reducing the symmetry of the acoustic back cavity access. This paper highlights the overall requirement of considering housing geometries and their influence on acoustic behavior for bio-inspired directional microphones

On the Analysis and Detection of Flames Withan Asynchronous Spiking Image Sensor

We have investigated the capabilities of a customasynchronous spiking image sensor operating in the NearInfrared band to study flame radiation emissions, monitortheir transient activity, and detect their presence. Asynchronoussensors have inherent capabilities, i.e., good temporal resolution,high dynamic range, and low data redundancy. This makesthem competitive against infrared (IR) cameras and CMOSframe-based NIR imagers. In this paper, we analyze, discuss,and compare the experimental data measured with our sensoragainst results obtained with conventional devices. A set ofmeasurements have been taken to study the flame emissionlevels and their transient variations. Moreover, a flame detectionalgorithm, adapted to our sensor asynchronous outputs, has beendeveloped. Results show that asynchronous spiking sensors havean excellent potential for flame analysis and monitoring.Universidad de Cádiz PR2016-07Ministerio de Economía y Competitividad TEC2015-66878-C3-1-RJunta de Andalucía TIC 2012-2338Office of Naval Research (USA) N00014141035