Acoustic beamforming for noise source localization - Reviews, methodology and applications

The Global Positioning System (GPS) can be readily used for outdoor localization, but GPS signals are degraded in indoor environments. How to develop a robust and accurate indoor localization system is an emergent task. In this paper, we propose a smartphone inertial sensor-based indoor localization and tracking system with occasional iBeacon corrections. Some important issues in a smartphone-based pedestrian dead reckoning (PDR) approach, i.e., step detection, walking direction estimation, and initial point estimation, are studied. One problem of the PDR approach is the drift with walking distance. We apply a recent technology, iBeacon, to occasionally calibrate the drift of the PDR approach. By analyzing iBeacon measurements, we define an efficient calibration range where an extended Kalman filter is utilized. The proposed localization and tracking system can be implemented in resource-limited smartphones. To evaluate the performance of the proposed approach, real experiments under two different environments have been conducted. The experimental results demonstrated the effectiveness of the proposed approach. We also tested the localization accuracy with respect to the number of iBeacons.

Smartphone Inertial Sensor-Based Indoor Localization and Tracking With iBeacon Corrections

Unlike traditional networked embedded systems, the Internet of Things interconnects heterogeneous devices from various manufacturers with diverse functionalities. To foster the emergence of novel applications, this vast infrastructure requires a common application layer. As a single global standard for all device types and application domains is impracticable, we propose an architecture where the infrastructure is agnostic of applications and application development is fully decoupled from the embedded domain. In our design, the application logic of devices is running on application servers, while thin servers embedded into devices export only their elementary functionality using REST resources. In this paper, we present our design goals and preliminary results of this approach, featuring the Californium (Cf) CoAP framework.

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Moving Application Logic from the Firmware to the Cloud: Towards the Thin Server Architecture for the Internet of Things

In recent years, the improvement of wireless protocols, the development of cloud services and the lower cost of hardware have started a new era for smart homes. One such enabling technologies is fog computing, which extends cloud computing to the edge of a network allowing for developing novel Internet of Things (IoT) applications and services. Under the IoT fog computing paradigm, IoT gateways are usually utilized to exchange messages with IoT nodes and a cloud. WiFi and ZigBee stand out as preferred communication technologies for smart homes. WiFi has become very popular, but it has a limited application due to its high energy consumption and the lack of standard mesh networking capabilities for low-power devices. For such reasons, ZigBee was selected by many manufacturers for developing wireless home automation devices. As a consequence, these technologies may coexist in the 2.4 GHz band, which leads to collisions, lower speed rates and increased communications latencies. This article presents ZiWi, a distributed fog computing Home Automation System (HAS) that allows for carrying out seamless communications among ZigBee and WiFi devices. This approach diverges from traditional home automation systems, which often rely on expensive central controllers. In addition, to ease the platform’s building process, whenever possible, the system makes use of open-source software (all the code of the nodes is available on GitHub) and Commercial Off-The-Shelf (COTS) hardware. The initial results, which were obtained in a number of representative home scenarios, show that the developed fog services respond several times faster than the evaluated cloud services, and that cross-interference has to be taken seriously to prevent collisions. In addition, the current consumption of ZiWi’s nodes was measured, showing the impact of encryption mechanisms.

Design, Implementation and Practical Evaluation of an IoT Home Automation System for Fog Computing Applications Based on MQTT and ZigBee-WiFi Sensor Nodes.

Demand side management (DSM) will play a significant role in the future smart grid by managing loads in a smart way. DSM programs, realized via home energy management systems for smart cities, provide many benefits; consumers enjoy electricity price savings and utility operates at reduced peak demand. In this paper, evolutionary algorithms-based (binary particle swarm optimization, genetic algorithm, and cuckoo search) DSM model for scheduling the appliances of residential users is presented. The model is simulated in time of use pricing environment for three cases: 1) traditional homes; 2) smart homes; and 3) smart homes with renewable energy sources. Simulation results show that the proposed model optimally schedules the appliances resulting in electricity bill and peaks reductions.

An Intelligent Load Management System With Renewable Energy Integration for Smart Homes

Sound source localization is a well-researched subject with applications ranging from localizing sniper fire in urban battlefields to cataloging wildlife in rural areas. One critical application is the localization of noise pollution sources in urban environments, due to an increasing body of evidence linking noise pollution to adverse effects on human health. Current noise mapping techniques often fail to accurately identify noise pollution sources, because they rely on the interpolation of a limited number of scattered sound sensors. Aiming to produce accurate noise pollution maps, we developed the SoundCompass, a low-cost sound sensor capable of measuring local noise levels and sound field directionality. Our first prototype is composed of a sensor array of 52 Microelectromechanical systems (MEMS) microphones, an inertial measuring unit and a low-power field-programmable gate array (FPGA). This article presents the SoundCompass's hardware and firmware design together with a data fusion technique that exploits the sensing capabilities of the SoundCompass in a wireless sensor network to localize noise pollution sources. Live tests produced a sound source localization accuracy of a few centimeters in a 25-m2 anechoic chamber, while simulation results accurately located up to five broadband sound sources in a 10,000-m2 open field.

https://www.mdpi.com/1424-8220/14/2/1918/pdf

SoundCompass: A Distributed MEMS Microphone Array-Based Sensor for Sound Source Localization

Indoor localization of persons and objects poses a great engineering challenge. Previously developed localization systems demonstrate the use of wideband techniques in ultrasound ranging systems. Direct sequence and frequency hopping spread spectrum ultrasound signals have been proven to achieve a high level of accuracy. A novel ranging method using the frequency hopping spread spectrum with finite impulse response filtering will be investigated and compared against the direct sequence spread spectrum. In the first setup, distances are estimated in a single-access environment, while in the second setup, two senders and one receiver are used. During the experiments, the micro-electromechanical systems are used as ultrasonic sensors, while the senders were implemented using field programmable gate arrays. Results show that in a single-access environment, the direct sequence spread spectrum method offers slightly better accuracy and precision performance compared to the frequency hopping spread spectrum. When two senders are used, measurements point out that the frequency hopping spread spectrum is more robust to near-far effects than the direct sequence spread spectrum.

https://www.mdpi.com/1424-8220/14/2/3172/pdf

Ultrasonic multiple-access ranging system using spread spectrum and MEMS technology for indoor localization.

Home Automation (HA) products based on IEEE 802.15.4 and ZigBee, both low power wireless communication standards, are starting to appear on the market. Most of these products use the 2.4GHz Industrial Scientific Medical (ISM) band, sharing the wireless spectrum with several other ubiquitous technologies such as Bluetooth, cordless phones, microwaves ovens and WiFi. The potential for cross technology interference exists and it is a looming threat to the success of new HA products based on the IEEE 802.15.4 standard. We developed a ZigBee Home Automation line of products for the Belgium market and therefore decided to evaluate the robustness of our products in the face of cross technology interference in the crowded 2.4 GHz band. We exposed our product, in a controlled laboratory setting, to increasing levels of WiFi interference and measured its performance. This paper summarizes our findings and presents recommendations and a methodology to measure and avoid WiFi interference while deploying and installing ZigBee based products in a home setting. While ZigBee products can successfully withstand interference from microwave ovens and Bluetooth devices, they are still vulnerable to high load WiFi traffic. ZigBee and WiFi can peacefully coexist in the home environment as long as certain basic precautions are taken.

Coexistence with WiFi for a Home Automation ZigBee product

MEMS microphones are miniature microphones, usually in the form of a surface mount device, which use a micromachined pressure-sensitive diaphragm as a way to pick up sound waves. They are steadily becoming more powerful and space efficient, and their audio data quality is already equal to or better than the previously ubiquitous electret condenser microphones. These characteristics, together with their low cost and small-form factor, makes them ideal for wireless applications in consumer products and wireless sensor networks. This chapter explores the uses and potential of MEMS microphones in wireless consumer products, acoustic noise wireless sensor networks, and sound source localization applications with microphone arrays.

MEMS microphones for wireless applications

In this paper we present a complete modular PCB manufacturing process on fablab scale that is compliant with current PCB manufacturing standards. This includes, but is not limited to, a minimum track width of 8 mil, a minimum clearance of 6 mil, plated and non plated holes, a solder resist, surface finish and component overlay. We modularize industrial manufacturing processes and discuss advantages and disadvantages of production techniques for every phase. We then proceed to discuss the relevance and added value of every phase in the manufacturing process and their usefulness in a fablab context. Production techniques are evaluated regarding complexity, overhead, safety, required time, and environmental concerns. To ensure practical feasibility of the presented techniques, the manufacturing process is benchmarked in FablabXL and aims to be a practical reference for implementing or extending PCB manufacturing activities in fablabs.

Jelmer Tiete

Papers

SoundCompass: A Distributed MEMS Microphone Array-Based Sensor for Sound Source Localization

Ultrasonic multiple-access ranging system using spread spectrum and MEMS technology for indoor localization.

Coexistence with WiFi for a Home Automation ZigBee product

MEMS microphones for wireless applications

Experimental Analysis of Small Scale PCB Manufacturing Techniques for Fablabs