Stephen J. Bellis

Development of field programmable modular wireless sensor network nodes for ambient systems

The goal of this work is to fabricate robust, miniature, wireless sensor modules. These provide an enabling technology platform to conduct research in creating ambient systems, through implementing wireless sensor network applications. The approach taken is to partition the wireless sensor module into a series of layers with area 25mmx25mm. This modular approach has resulted in the specification of a series of layers, including a field programmable gate array layer for digital signal processing type operations, forming the initial elements of the 25mm sensor node toolkit that can be programmed for use with different sensors depending on application. This paper highlights the development of the sensor, processing, communication and power layers, and the connection approach used to form a robust modular system. Comparisons are made with other wireless sensor nodes and application examples are given.

A 3D miniaturised programmable transceiver

Purpose – To describe the development of a three dimensional programmable transceiver system of modular design for use as a development tool for a variety of wireless sensor node applications.Design/methodology/approach – As a stepping‐stone towards the development of wireless nodes, sensor networks programme was put in place to develop a 25 mm cube module, which was modular in construction, programmable and miniaturised in form factor. This was to facilitate the development of wireless sensor networks for a variety of different applications. The nodes are used as a platform for sensing and actuating through various parameters, for use in scalable, reconfigurable distributed autonomous sensing networks in a number of research projects currently underway in the Tyndall Institute, as well as other institutes and in a variety of research programs in the area of wireless sensor networks.Findings – The modular construction enables the heterogeneous implementation of a variety of technologies required in the ar...

FPGA implementation of spiking neural networks - an initial step towards building tangible collaborative autonomous agents

This work contains the results of an initial study into the FPGA implementation of a spiking neural network. This work was undertaken as a task in a project that aims to design and develop a new kind of tangible collaborative autonomous agent. The project intends to exploit/investigate methods for engineering emergent collective behaviour in large societies of actual miniature agents that can learn and evolve. Such multi-agent systems could be used to detect and collectively repair faults in a variety of applications where it is difficult for humans to gain access, such as fluidic environments found in critical components of material/industrial systems. The initial achievement of implementation of a spiking neural network on a FPGA hardware platform and results of a robotic wall following task are discussed by comparison with software driven robots and simulations.

The DSYS25 sensor platform

In this demonstration, a new sensor platform named DSYS25 is presented. The platform has a unique hardware design and runs a customized version of the TinyOS operating system. Transceiver hardware and packaging distinguish the D-Systems platform from other available designs.

High-performance computing for real-time spectral estimation

Abstract This paper presents two separate investigations into the real-time implementation of the modified covariance spectral estimator: one comparing performances on digital signal processors, the TMS320C40, and the recently released ADSP2016x (SHARC); another using application-specific custom circuitry. The advantages and disadvantages of each of these different approaches are reviewed, resulting in the design of a field-programmable gate array/digital signal processor-based high-performance system that combines the hardware and software approaches. In conjunction with pulsed Doppler ultrasound blood-flow detectors, the spectral estimator offers increased sensitivity in the non-invasive detection of arterial disease.

A hybrid network of autonomous sensor nodes

A robust hybrid intelligent system architecture is being proposed. This communication discusses the prospect of using NMRCs 25mm wireless sensor node in conjunction with other sensor motes. The NMRC node is the Institutes specification for future autonomous transducer nodes in ubiquitous computational networks that will drive the vision of Ambient Intelligence (AmI). A comparative study among different motes with NMRCs node has been performed in order to define a hybrid autonomous sensor network that includes all of them. The main points to differentiate between the NMRC modules and the others are reconfigurability of the module, dense interconnectivity between layers and intensive signal processing capability.

OPTIMAL SYSTOLIC ARRAYS FOR REAL-TIME IMPLEMENTATION OF THE MODIFIED COVARIANCE SPECTRAL ESTIMATOR

The Modified Covariance method of spectral estimation, proposed as a replacement of the conventional short term Fourier transform for use with pulsed Doppler ultrasound blood flow detectors in order to improve time/frequency resolution, is computationally far more demanding. The use of an application specific architecture for real-time implementation is of interest. A cost/benefit selection of systolic arrays, firstly for a matrix solution method with suitable bus width and secondly for calculation of covariance matrix elements, led to the choice of Cholesky matrix decomposition, 12 bit bus width and a bi-linear systolic array designed using a data dependence graph method.

A CORDIC Arctangent FPGA Implementation for a High-Speed 3D-Camera System

This paper presents the design and FPGA implementation of a pipelined CORDIC arctangent unit suitable for use in a 3D camera system. The end use for this application is in the assembly of printed circuit boards where there is a need for high-speed 3D height inspection of solder paste. FPGAs are chosen as the implementation platform, firstly for their quick turnaround to a final prototype; secondly for their reprogrammability to meet advances in algorithm design via software rather than hardware; thirdly footprint compatible higher speed grade FPGAs can be used to adapt the system to improved sensor technologies as they become available; finally the latest FPGAs offer a wide range of resources, including SDRAM drivers, ZBT SRAM drivers, fast carry logic and interfaces such as LVTTL and LVDS.

An inertial measurement unit (IMU) for an autonomous wireless sensor network

This paper will present the work done in designing and fabricating an autonomous inertial measurement unit (IMU) panel for a novel 25mm wireless sensor network platform. This panel increases the sensory capabilities of each node allowing the orientation of each node to be completely realised. As part of the NMRCs technology development there is a drive towards wireless nodes for sensor networks of volume in the sub 5mm region (Barton et al., 2003; Barton et al., 2004). As a stepping stone towards this goal, the target objectives for the development of a 25mm cube module were to develop, a low volume prototyping and experimentation platform. This is for use as a platform for sensing and actuating through various parameters, for use in scalable, reconfigurable distributed autonomous sensing networks in a number of research projects currently underway in the NMRC. This paper outlines the development of the system with particular emphasis on the IMU layer. The total system is packaged in a modular 25mm cubed form factor which gives the capability for the module to be utilised in a wide variety of projects incorporating a multitude of actuators/sensors in miniaturised, mobile, autonomous systems.

Configurable Processing for Real-Time Spectral Estimation

Abstract This paper presents a system for real-time implementation of the fourth order Modified Covariance spectral estimator, which, when used in conjunction with pulsed Doppler blood flow detectors, has been shown to offer increased sensitivity in atherosclerotic disease detection. The computational burden incurred with the Modified Covariance method is considerably greater than that of the conventional FFT method. This has led to separate studies to evaluate the cost and performance of firstly, transputer/DSP based platforms and secondly, application specific custom circuitry, for implementation of the algorithm in real-time. The advantages and disadvantages of each of these different approaches are reviewed in this paper resulting in the design of a combined custom/DSP based system.