Roberto Sannino

Performance Considerations for an Embedded Implementation of OMA DRM 2

As digital content services gain importance in the mobile world, digital rights management (DRM) applications will become a key component of mobile terminals. The paper examines the effect dedicated hardware macros for specific cryptographic functions have on the performance of a mobile terminal that supports version 2 of the open standard for DRM defined by the Open Mobile Alliance (OMA). Following a general description of the standard, the paper contains a detailed analysis of the cryptographic operations that have to be carried out before protected content can be accessed. The combination of this analysis with data on execution times for specific algorithms realized in hardware and software has made it possible to build a model which has allowed us to assert that hardware acceleration for specific cryptographic algorithms can significantly reduce the impact DRM has on a mobile terminals processing performance and battery life.

BlueVoice: Voice communications over Bluetooth Low Energy in the Internet of Things scenario

Abstract Bluetooth Low Energy (Bluetooth LE) is a key technology in the envisioned Internet of Things (IoT) scenario. In fact, its extremely low-power characteristics make it one of the most suitable solutions to enable wireless communications among battery powered IoT objects ubiquitously deployed in the field with the aim of building smart environments. Although Bluetooth LE specification targets a specific set of applications mainly devoted to monitoring purposes, innovative solutions can lead to the adoption of such technology in different applications, such as multimedia streaming, allowing IoT objects to exploit new functionalities. In this direction this article presents BlueVoice, an application targeted to Bluetooth LE devices to enable speech streaming services. In the article BlueVoice is presented by first detailing the services set extension needed to support the new envisioned multimedia service, then a description of application choices is given, followed by an evaluation of its performance in real IoT objects. Thanks to the selected speech encoding technique, connection design choices and packetization strategies, BlueVoice application requires a communication bandwidth of 64.3 kbps to transmit audio at 16 kHz in ADPCM format. BlueVoice performance has been evaluated in terms of power consumption, memory and processing requirements, showing feasibility of the developed solution in resource constrained devices, thus confirming the correct choices in the application design. The set of performance information obtained show that BlueVoice is a viable solution to enable speech communications in ubiquitous wireless IoT nodes based on the Bluetooth LE technology.

Modular Low-Cost Robotics: What Communication Infrastructure?

Abstract In this paper we present a methodological approach for the development and fast prototyping of robotics applications targeted to the mass market. According to this approach, a robot is considered as a distributed hardware and software system, in which the components are “smart devices”, i.e., hardware modules with onboard computation. Our proposal aims, through a modular architecture, at massive hardware/software reuse and fast prototyping. We suggest to consider a robotic application as a distributed control system, where a set of basic modules (e.g., sensors, actuators, controllers) is interconnected in a plug-and-play way by means of a common physical communication interface. The requirements of such physical interface are elicited in the paper, starting from three real case studies, and a discussion about a proposed solution is provided.

Multichannel speech enhancement using MEMS microphones

In this work, we investigate the efficacy of Micro Electro-Mechanical System (MEMS) microphones, a newly developed technology of very compact sensors, for multichannel speech enhancement. Experiments are conducted on real speech data collected using a MEMS microphone array. First, the effectiveness of the array geometry for noise suppression is explored, using a new corpus containing speech recorded in diffuse and localized noise fields with a MEMS microphone array configured in linear and hexagonal array geometries. Our results indicate superior performance of the hexagonal geometry. Then, MEMS microphones are compared to Electret Condenser Microphones (ECMs), using the ATHENA database, which contains speech recorded in realistic smart home noise conditions with hexagonal-type arrays of both microphone types. MEMS microphones exhibit performance similar to ECMs. Good performance, versatility in placement, small size, and low cost, make MEMS microphones attractive for multichannel speech processing.

Code compression for VLIW embedded processors

The implementation of processors for embedded systems implies various issues: main constraints are cost, power dissipation and die area. On the other side, new terminals perform functions that require more computational flexibility and effort. Long code streams must be loaded into memories, which are expensive and power consuming, to run on DSPs or CPUs. To overcome this issue, the “SlimCode” proprietary algorithm presented in this paper (patent pending technology) can reduce the dimensions of the program memory. It can run offline and work directly on the binary code the compiler generates, by compressing it and creating a new binary file, about 40% smaller than the original one, to be loaded into the program memory of the processor. The decompression unit will be a small ASIC, placed between the Memory Controller and the System bus of the processor, keeping unchanged the internal CPU architecture: this implies that the methodology is completely transparent to the core. We present comparisons versus the state-of-the-art IBM Codepack algorithm, along with its architectural implementation into the ST200 VLIW family core.

Low cost smartcams design

Nowadays, digital image processing is the most common form of image processing. Digital image processing makes it possible to enhance image features of interest while attenuating detail irrelevant to a given application, and then extract useful information about the scene from the enhanced image. For instance, digital cameras usually include dedicated digital image processing chips in order to improve at real-time the quality of images directly on-board. This paper proposes a very low cost vision system that is able to perform image processing tasks with a wide set of digital image processing algorithms, that have been specifically optimized for the proposed architecture. Some of these algorithms can be used to detect and to track a set of previously acquired targets. Finally, the proposed solution has been proved to be an effective solution even when applied to real-world case studies, such as the detection and the tracking of test-tubes in a medical environment.

A real-time communication protocol for interconnecting robotic smart devices

A communication system for robotics application should allow fast exchange of real-time data for low level robot control and large amount of data for high level algorithms like intelligent vision or map building. Ethernet seems to be the perfect candidate for the low level communication interface because of its large diffusion, high bandwidth and low cost. This paper describes a real-time communication protocol for interconnecting robotic smart devices. Some comparison with existing standard are also presented.

Multistage block-matching motion estimation for superresolution video reconstruction

The performance of superresolution video enhancement relies heavily on the robustness and accuracy of motion estimation techniques. In this paper, we propose a novel and efficient block matching motion estimation algorithm suitable for estimating general motion existing in low resolution video frames. We exploit the spatial correlations between motion vectors and apply a coarse-to-fine multi-stage scheme to get the dense motion fields. We incorporate our motion estimation technique into the Projection Onto Convex Sets (POCS) superresolution framework. Experimental results show that the resulting high resolution images yield visual sharper enhanced images with significant PSNR improvement.

Efficient Continuous Beam Steering for Planar Arrays of Differential Microphones

Performing continuous beam steering, from planar arrays of high-order differential microphones, is not trivial. The main problem is that shape-preserving beams can be steered only in a finite set of privileged directions, which depend on the position and the number of physical microphones. In this letter, we propose a simple and computationally inexpensive method for alleviating this problem using planar microphone arrays. Given two identical reference beams pointing in two different directions, we show how to build a beam of nearly constant shape, which can be continuously steered between such two directions. The proposed method, unlike the diffused steering approaches based on linear combinations of eigenbeams (spherical harmonics), is applicable to planar arrays also if we deal with beams characterized by high-order polar patterns. Using the coefficients of the Fourier series of the polar patterns, we also show how to find a tradeoff between shape invariance of the steered beam, and maximum angular displacement between the two reference beams. We show the effectiveness of the proposed method through the analysis of models based on first-, second-, and third-order differential microphones.

Wearable speech enhancement system based on MEMS microphone array for disabled people

Disabled people, especially the ones with motor skill impairments, have difficulties in interacting with personal computers and smartphones. Indeed Automatic Speech Recognition (ASR) could be helpful for those people, but its limited in scenarios not affected by environmental noise that can decrease performance of the recognition, limiting user experience. We propose a speech enhancement system based on MEMS microphone array and a digital signal processor in order to increase signal-to-noise ratio (SNR) of the users voice. The audio delay between microphones is exploited by the array using the Differential Microphone Array (DMA) and an Adaptive Noise Reduction techniques. In such way the system can obtain an increment in SNR about 16.5 dB, when noise and voice come from opposite directions. A voice activity detection (VAD) block recognizes when the user speaks and sends the data to a cloud-based ASR system. Due to the small array size, the embedded system can be integrated in a wearable device. Theoretical analysis and in-system measurements prove the effectiveness of the proposed solution.