Benchmarking Low-Resource Device Test-Beds for Real-Time Acoustic Data
نویسندگان
چکیده
The EAR-IT project relies on 2 test-beds to demonstrate the use of acoustic data in smart environments: the smart city SmartSantander test-bed and the smart building HobNet test-beds. In this paper, we take a benchmarking approach to qualify the various EAR-IT test-bed based on WSN and IoT nodes with IEEE 802.15.4 radio technology. We will highlight the main performance bottlenecks when it comes to support transmission of acoustic data. We will also consider audio quality and energy aspects as part of our benchmark methodology in order to provide both performance and usability indicators. Experimentations of multi-hop acoustic data transmissions on the SmartSantander test-bed will be presented and we will demonstrate that streaming acoustic data can be realized in a multi-hop manner on low-resource device infrastructures.
منابع مشابه
A Generalization of Initial Conditions in Benchmarking of Economic Time-Series by Additive and Proportional Denton Methods
The paper presents unified analytical solution for combining high-frequency and low-frequency economic time-series by additive and proportional Denton methods with parametrical dependence on the initial values of variable and indicator in evident form. This solution spans Denton’s original and Cholette’s advanced benchmarking initial conditions as the subcases. Computational complexity of the o...
متن کاملMeasuring Performance, Estimating Most Productive Scale Size, and Benchmarking of Hospitals Using DEA Approach: A Case Study in Iran
Background and Objectives: The goal of current study is to evaluate the performance of hospitals and their departments. This manuscript aimed at estimation of the most productive scale size (MPSS), returns to scale (RTS), and benchmarking for inefficient hospitals and their departments. Methods: The radial and non-radial data envelopment analysis (DEA) ap...
متن کاملReal-time acoustic tomography system and the experience of Caspian current sea monitoring
The Acoustic Tomography (AT) systems are used to monitor long-term and continuous flow in rivers, seas and oceans. One of the disadvantages of existing systems in Iran is the inability of real-time/automated measurements. In this study, by adding a raspberry Pi computer to the system and performing the required programming, it was possible to do online monitoring. The data are transferred to th...
متن کاملOn the Application of the Raspberry Pi as an Advanced Acoustic Sensor Network for Noise Monitoring
The concept of Smart Cities and the monitoring of environmental parameters is an area of research that has attracted scientific attention during the last decade. These environmental parameters are well-known as important factors in their affection towards people. Massive monitoring of this kind of parameters in cities is an expensive and complex task. Recent technologies of low-cost computing a...
متن کاملTransfer Learning and Distillation Techniques to Improve the Acoustic Modeling of Low Resource Languages
Deep neural networks (DNN) require large amount of training data to build robust acoustic models for speech recognition tasks. Our work is intended in improving the low-resource language acoustic model to reach a performance comparable to that of a high-resource scenario with the help of data/model parameters from other high-resource languages. we explore transfer learning and distillation meth...
متن کامل