Final Report Summary - WILDCRAFT (Wireless Smart Distributed end System for Aircraft)
Executive Summary:
WILDCRAFT proposes the design, development and testing of a proof-of-concept demonstrator of a Wireless Sensor Network (WSN) aimed at applications in the aerospace industry. The continuous pressure on aircraft manufacturers to produce better and more secure aircrafts has led to increasing costs in maintenance and monitoring procedures that are being performed at given time intervals to assess the state of an aircraft. Wireless Sensor Networks (WSN) allows the continuous monitoring of critical variables of the operation of an aircraft, and as such they are able to issue early warning of a possible problem for immediate repairing.
WILDCRAFT is paying attention to data fusion techniques needed for obtaining an "abstract sensor" from the measurements taken by a multiplicity of sensors deployed in a specific part in an aircraft. To that end we are going to study the most suitable algorithms to infer, estimate or summarize the state of the physical variable being measured. The designed algorithms will be implemented in a FPGA platform. In WILDCRAFT we are also considering the safety critical nature of any on-board system in an aircraft.
The set of safety requirements of the system will be compiled and used for the specification, design and development of the building blocks of the system: sensors, energy harvesting, RF transceiver and microprocessor, and the corresponding levels of software and programmable hardware blocks.
Project Context and Objectives:
The project's objectives are:
• To define an architecture for a WSN able to operate in an aircraft environment. Among the characteristics we are seeking for the WSN are:
o Range of communications between nodes must be at least the size of a typical aircraft.
o Worldwide deployment of the system. This is particularly important if RF communications are used.
o Flexible architecture that allows the installation of different kind of sensors with minimal changes (preferably, software changes)
o The definition of the architecture must take into account functional specifications applicable to the aerospace industry with regard to weight, RF emissions and power consumption.
o Low Power Consumption. Evaluate the impact of energy harvesting and power management in the total power consumption of the nodes.
• To take into account the Safety Critical specifications imposed by the aerospace industry in the design of such a system. A risk assessment will be made to confront possible problems at all level of the device life cycle: design, validation and operation.
• To develop a demonstrator of the WSN using several sensors nodes (temperature, strain gauges, vibrations) and one global computation unit that will gather and process the data obtained from the sensors in order to show the state of the aircraft's parts by presenting them in a unified way.
• The final objective of WILDCRAFT is to serve as a fully automated way of inspecting the state of an aircraft structure and to achieve that it will be necessary to process a large amount of data in an intelligent way. WILDCRAFT will be using the inherent redundancy of WSNs to augment the overall fault tolerance of the system by employing data fusion techniques that can be implemented both at the node level and also at a global level to produce values that can be thought as a measure from an "abstract sensor" that represent the measures from all de WSN.
Project Results:
After the study and analysis of the functional requirement of the system regarding data rate, number of sensor nodes and type of sensors, frequency bands, power consumption and reliability issues, we have reached the following design decisions for the different parts of the WILDCRAFT system.
• Sensor Node Architecture. The central component of the node is the MSP430 microprocessor that will manage and monitor all the functionality provided by the node: sensoring, power management and wireless communications. The hardware and software architectures are given in Figure 1 and Figure 3 respectively. Moreover an estimated budget of the components to be used in the sensor node is provided for reference only (the prices are usually being quoted for small quantities).
Sensors. The components selected for acceleration, temperature and humidity present a complete solution from the sensor itself, to the signal conditioning, analog-to-digital conversion and digital interfacing. An integrated solution that saves board space, simplifies PCB layout and routing while providing a very good resolution and variation ranges for the given quantity, very good power consumption behaviour and sampling rates can be programmed from the microcontroller. There is no integrated solution for the strain gauge sensors that measure deformations. An IC (MAX1452) has been selected for conditioning the output signals of the Wheastone Bridge. This IC is an analog circuit that has a programmable amplifier and several offset compensation blocks that can be controlled digitally from a microcontroller. The analog-to-digital of the strain gauge signal conversion will be made on the microcontroller’s ADC. The sampling frequency has been estimated as near to 100-200 Hz taking into account the typical modes of vibration in aircraft’s structures.
Energy Harvesting. We have selected a thermal harvester as the source of additional energy in our system. Given the environmental conditions in which the system will operate we think that this source is the most readily available. The harvester circuitry has been designed to include the step-up converter and the battery charger. Power supply status indicators have also been included to measure the power provided by the harvester, battery fuel gauges and the power consumption of the sensor node.
Programming & Testing Circuitry. A serial interface and a JTAG connector have been added to the sensor node for testing and debugging purposes. Additionally we have included current sense circuitry to measure the power consumption of the sensor node under different modes of operation. The current sense is an analog circuit that is sampled by the A/D converter of the microcontroller.
• Global Node Architecture. The architecture of the global node has been divided into a coordinating node that has direct access to the Tx/Rx of the WSN and a computation node for post-processing the data obtained from the sensors. The block diagram is given in Figure 2. The main processor is an IMX51 Cortex-A8 ARM processor from Freescale. This device will hold a Linux OS that provides support for external devices like USB and micro-USB, SD card and ethernet connectivity. The processor interfaces with two elements of the global node: the WSN coordination node (see below) vi a SPI interface and the global computation element in a Spartan6 FPGA using the EIM (Extension Interface Module)
WSN Coordination Node. Its architecture is the same as other sensor node. The functionality is, of course, different providing network coordination and keeping synchronization with the rest of the sensor nodes. Their main task is to gather the data from the different sensors. The coordinating node has a SPI interface with the main processor (see next)
Global Computation. The computation node consists of an ARM processor (iMX51 @ 800MHz) and a FPGA (Spartan6 LX9) for hardware acceleration. The ARM processor obtains the data from the sensors via a SPI interface. Although the ARM device is capable of fast processing large amounts of data, the FPGA is serving for accelerating certain very demanding tasks. In our system the FPGA is currently performing two types of operations: a 1024-point FFT and 512-points cross-correlations.
- The processor handles the operation of the FPGA via a special memory interface that access to registers inside the FPGA to inform about the tasks that must be performed. That interface between processor and FPGA is made using very simple C code, so the operations in the FPGA are very transparent from the user point o view.
• Communications/Topology/Network Operation. The architecture of the wireless communication interface is based on the 802.15.4 standard in the 2.4GHz band. The chipsets that will be used in the sensor node are the CC2520 Transceiver and the MSP430 microcontroller, both from Texas Instrument. We have selected a dual-chip solution instead of a SoC solution because we wanted to have flexibility in the peripherals needed for the sensor, processing power and internal memory that a microcontroller has, as opposed to a single-chip solution that offers very limited performance. The network topology selected is a star-tree topology where each node communicates directly or through router nodes with the global node. The operation of the sensor network is such that each node obtains the measures from the sensors at the same time, but the data transmission is made sequentially one node at a time, so the whole bandwidth is available for the nodes, without additional interferences from other nodes. A node synchronization strategy must be followed in order to ensure the time-coherence of the data obtained from the sensors and the time-division operation of the wireless media.
Power Consumption and Battery Operation of the Sensor Nodes.
• Software Architecture. The proposed architecture is based on a multi-layered architecture with different software components. Low-level components (middleware) execute basic tasks, while higher level components use the API offered by the middleware to achieve more complicated functionality while maintaining efficiency and simplicity of coding. The basic functionality of our middleware system is to hide the low-level details of the sensor node (e.g. manage the system resources efficiently) by providing a clear interface to applications developed at the highest level.
o WSN Nodes. Sensor Node & Coordination Node
o Global Computation Processor.
• Testing and validation of the WSN
Based on these design decisions we have obtained the following results:
- A WSN consisting of several nodes. The WSN was demonstrated to work in a aircraft environment and work under different Duty-Cycle, different sensor options, sensing power state of the WSN (battery gauges), able to adapt to changing conditions in the RF links (power adaptation thanks to monitorization of RSSI values)
- A global computation node able to post-process data from the sensors and store data for further analysis. Large storage capability thanks to a SD card interface. External connection using Ethernet, easy and secure access thanks to ssh protocols.
- Analysis of functional specifications and requirements of the system in terms of bandwidth, data rate, frequency bands, power consumption and protocol stack to develop.
- Selection of a WSN architecture: protocol stack, frequency bands and configuration of the WSN
- Architecture of the sensor node: selection of components for the different sensors, the Tx/Rx and the software stack, energy harvesting and battery gauge circuitry. Methods for testing and measurements (serial link and power measurements)
- Architecture of the global node: selection of components, separation of global computation and WSN coordination, external interfaces with external infrastructure.
- Design of the Sensor Node schematic and layout, test plan for the sensor node, API functions for configuring the sensors and accessing the sensor data from the microcontroller. Development of software routines to measure the power consumption of the sensor node.
- Design of the Global Node schematic and layout, test plans for the global node, implement and embedded Linux in the global computation processor (ARM), communication between ARM and WSN coordinator (MSP430), global computation hardware in FPGA.
- Design of a Software Architecture for the WSN: data encapsulation and packing (data from the sensor, timestamp, RSSI, battery gauges), WSN configuration and Setup, WSN synchronization, WSN node coordination and adaptation.
- Design of Firmware for Sensor Node and for the coordinator node:
- Design of Global Computation Routines in the ARM processor: WSN Setup, SPI communication with coordinating node, Communication with the FPGA and hardware acceleration, FFT and cross-correlation, Post-processing data from Sensors, Lowpass filtering and decimation
- Test Review in HAI facilities in Nov’13 consisted in proofing the feasibility of the work made and the preparation of the WSN toward a more extensive demo scenario at the end of the project.
- Definition of a demonstration scenario at HAI facilities. Deployment of the nodes, coordination from the global node, sensor data post-processing in the global computation hardware (ARM+FPGA) and interface via Ethernet with an external application that is able to store and visualize the data from the different sensors at different node locations and modify the WSN operation parameters.
Potential Impact:
1. POTENTIAL IMPACT
To understand the potential impact of a research project like WILDCRAFT we have to look at how other people, normal citizens, visualize our work. In our relations with mass-media explaining the objectives of WIDLCRAFT we have had the opportunity to grasp the concerns and opportunities that a development like WILDCRAFT would represent for them.
The idea of WILDCRAFT is to provide the aircrafts with a set of fixed sensors that can be deployed around the aircrafts, take measures of certain physical aspects of the aircraft’s structure and forward those measures wirelessly to a central unit that provide time-coherence and perform complicated algorithms with those measures. The ultimate objective of WILDCRAFT would be to be able to extract the exact state of the aircraft structure from those algorithms with several consequences:
• Increased observability of parameters in the aircraft.
• Increased capacity to detect potential problems in the aircraft’s structure or nearby apparatus.
• Early detection of potential problems before they can be detected by normal periodic checks.
• Avoid/delay maintenance actions if no problems are detected.
• Because of the above, reduction of maintenance costs and other associated costs like aircraft down time.
• Potential reduction in cabling due to the wireless nature of the communications, which leads to less weight and fuel consumption and emissions.
• Increase the perception of safety from the users.
In general, the public still perceives safety as the most important concern regarding aircrafts. Despite the fact the aviation industry is the most secure transport media by a large distance, that safety regulations are extremely good and that they are greatly enforced by the aviation authorities, accidents still occur and have a profound impact in the society as a whole.
It is a fact that most of the people in developed countries have access to state-of-art technology in their hands (thanks to smart-phones and tablets): almost ubiquitous access to worldwide wireless communications, worldwide localization algorithms, sensoring health information (heart-rate, etc.) People are increasingly aware of those technologies and are continuously using them, but at the same time these technologies provide a false sense of instant availability. In this sense, we think there is an increasing perception from the users that technology is not being used at its best in the transportation sector. Therefore, there is a need to correct that perception by:
• More information and education to users and citizens about the limitations of technology and abou the process of adoption and deployment of technologies in safety critical activities.
• Information to the users and citizens about the costs associated with the final deployment of safety critical devices and services.
• Make the user of an aircraft aware that state-of-the-art technologies are being used in the aircraft and that this is increasing its own safety. Of course, to increase the perception of safety must not be compromising the safety itself.
In order to deploy WILDCRAFT we have designed a Roadmap that was described in D1.11. In this deliverable we discussed the more critical technologies that must be targeted in order to full deployment. A summary of the conclusions is given here and shown in Tables 1 and 2. Based on this analysis we have found the following technologies as the most demanding issues for system like WILDCRAFT (in yellow in above tables):
1. Data Fusion Algorithms:
o Multidisciplinary Research (mechanical, electronics, information theory, digital signal processing, aeronautics, etc)
o Support from the industry must see real and tangible benefits.
2. Battery Technology:
o Specify their batteries in the environment conditions that apply for aerospace.
o Specify battery charging/discharging behaviour with high and low temperatures.
o Establish appropriate airworthiness standards for Li-Ion battery installations and to ensure, as required by CS 25.601 that these battery installations do not have hazardous or unreliable design characteristics.
3. Co-existence with other wireless technologies. There is a strong need for these studies to be made and guarantee that a sufficient availability of the WILDCRAFT system is achieved while not hampering the operation of other services.
4. Network Synchronization: Network Time error between the nodes must be <50s.
5. Algorithm Robustness and Reliability: more efficient reliable methods should be considered, since the reliability has a cost in terms of resource usage, energy wastage, bandwidth consumption and effective data rate. Optimal solution will be found based on thoroughly testing in real environment.
A roadmap for a prototype of WILDCRAFT is given in attached document
2. EXPLOITATION OF FOREGROUND
The exploitable foreground declared in WILDCRAFT has the purpose of protecting hardware and software developments completed during the course of the project.
CEIT has declared foreground of hardware devices (which includes schematics and layout) related to sensor and global nodes. The functionalities that that hardware is implementing are: wireless communications (Zigbee based RF transceiver and microcontroller), power management for harvesting and storage, strain gage sensor conditioning circuitry and accompanying software modules for configuring and controlling the sensor devices.
The purpose of the declared foreground is to leverage the know-how gained during the project to support other industrial activities that can make use of similar technologies such as WSN.
As a Research Institution the commercial exploitation of this foreground will be done mainly via:
• Research Projects with interested companies in sectors like energy (smart grids, maintenance systems), civil engineering (structural health monitoring based WSN) or automotive.
• Creation of spin-off companies that can commercialize not only the foreground but at the same time provides specific services for customers in the above mentioned sectors.
Currently CEIT is participating in projects in collaboration with local industries (energy sector) in which the foreground declared here will be applied.
INTE declared foreground of software modules running in microcontroller devices. The functionalities provided are power management strategies for WSN, WSN Topology management and synchronization, automatic power transmission control, communication between ARM and MSP430 and tester applications for management and configuration of the WSN. INTE is a software company that offers specific solutions for satellite operators and installers: carrier spectrum monitoring, demodulation under carrier interference, automated calibration etc. Additionally Integrasys has already implemented WSN for monitoring plant factory for civil engineering. The purpose of the foreground presented by Integrasys is to diversify the activities of the company and targeting other sectors related to communications but in the topic of the smart grids and maintenance systems in general. In these areas WSN represent a good opportunity to increase and enhance the portfolio of products and services that Integrasys currently holds. The activities of Integrasys towards achieving these objectives involve a continuous presence in panels and committees at the European level promoting the use of embedded systems.
The additional research needed must accommodate the current foreground declared to the specific conditions of the sector: electrical specifications (power consumption requirements), functional specifications (type of sensors require), communications (bandwidth, frequency bands, latency, data rate, etc). A detailed analysis of needed further research has been detailed in deliverable D1.11. In that document we used two indicators:
• The Enabling Factor Rank (EFR) is the importance of that technology in the deployment of WILDCRAFT. The lower this number is, the more important it is.
• The estimated Time Frame (TF) at which a solution will be found
As a result, we calculated the Priority Rank as the relation between the Time Frame and the Enabling Factor Rank (TF/EFR). This number tells us the priority of the technology in question. The summarized results are illustrated in the tables shown in attached document (more information can be seen in D1.11)
The tables below show the main dissemination activities in the media during the project.
In general, the mass media has shown a great interest in the results of WILDCRAFT. We have participated live in nationwide and regional programs (TV and radio) explaining the objectives of WILDCRAFT, showing our sensor nodes and how this can be used to improve the safety of aircrafts. Furthermore, the spanish digital newspapers elconfidencial.com published a report about WILDCRAFT and also the bbc.co.uk showed an interest in our work.
The link to all the published material (audio, video, etc) can be found in the tables given in the attached document.
WILDCRAFT was also presented to the Joint Technical Committee ISO/IEC JTC 1/WG7 on Sensor Networks (WGSN). The committee is formed by a number of experts from companies all around the world interested in the definition of protocols and techniques for WSN.
The partners have submitted a paper to the XXIX Conference on Design of Circuits and Integrated Systems (DCIS’14). The title of the paper is “Design Principles and Challenges for an Autonomous WSN for Structural Health Monitoring in Aircrafts”.
List of Websites:
http://www.wildcraft-eu.org/
Andoni Irizar, airizar@ceit.es
WILDCRAFT proposes the design, development and testing of a proof-of-concept demonstrator of a Wireless Sensor Network (WSN) aimed at applications in the aerospace industry. The continuous pressure on aircraft manufacturers to produce better and more secure aircrafts has led to increasing costs in maintenance and monitoring procedures that are being performed at given time intervals to assess the state of an aircraft. Wireless Sensor Networks (WSN) allows the continuous monitoring of critical variables of the operation of an aircraft, and as such they are able to issue early warning of a possible problem for immediate repairing.
WILDCRAFT is paying attention to data fusion techniques needed for obtaining an "abstract sensor" from the measurements taken by a multiplicity of sensors deployed in a specific part in an aircraft. To that end we are going to study the most suitable algorithms to infer, estimate or summarize the state of the physical variable being measured. The designed algorithms will be implemented in a FPGA platform. In WILDCRAFT we are also considering the safety critical nature of any on-board system in an aircraft.
The set of safety requirements of the system will be compiled and used for the specification, design and development of the building blocks of the system: sensors, energy harvesting, RF transceiver and microprocessor, and the corresponding levels of software and programmable hardware blocks.
Project Context and Objectives:
The project's objectives are:
• To define an architecture for a WSN able to operate in an aircraft environment. Among the characteristics we are seeking for the WSN are:
o Range of communications between nodes must be at least the size of a typical aircraft.
o Worldwide deployment of the system. This is particularly important if RF communications are used.
o Flexible architecture that allows the installation of different kind of sensors with minimal changes (preferably, software changes)
o The definition of the architecture must take into account functional specifications applicable to the aerospace industry with regard to weight, RF emissions and power consumption.
o Low Power Consumption. Evaluate the impact of energy harvesting and power management in the total power consumption of the nodes.
• To take into account the Safety Critical specifications imposed by the aerospace industry in the design of such a system. A risk assessment will be made to confront possible problems at all level of the device life cycle: design, validation and operation.
• To develop a demonstrator of the WSN using several sensors nodes (temperature, strain gauges, vibrations) and one global computation unit that will gather and process the data obtained from the sensors in order to show the state of the aircraft's parts by presenting them in a unified way.
• The final objective of WILDCRAFT is to serve as a fully automated way of inspecting the state of an aircraft structure and to achieve that it will be necessary to process a large amount of data in an intelligent way. WILDCRAFT will be using the inherent redundancy of WSNs to augment the overall fault tolerance of the system by employing data fusion techniques that can be implemented both at the node level and also at a global level to produce values that can be thought as a measure from an "abstract sensor" that represent the measures from all de WSN.
Project Results:
After the study and analysis of the functional requirement of the system regarding data rate, number of sensor nodes and type of sensors, frequency bands, power consumption and reliability issues, we have reached the following design decisions for the different parts of the WILDCRAFT system.
• Sensor Node Architecture. The central component of the node is the MSP430 microprocessor that will manage and monitor all the functionality provided by the node: sensoring, power management and wireless communications. The hardware and software architectures are given in Figure 1 and Figure 3 respectively. Moreover an estimated budget of the components to be used in the sensor node is provided for reference only (the prices are usually being quoted for small quantities).
Sensors. The components selected for acceleration, temperature and humidity present a complete solution from the sensor itself, to the signal conditioning, analog-to-digital conversion and digital interfacing. An integrated solution that saves board space, simplifies PCB layout and routing while providing a very good resolution and variation ranges for the given quantity, very good power consumption behaviour and sampling rates can be programmed from the microcontroller. There is no integrated solution for the strain gauge sensors that measure deformations. An IC (MAX1452) has been selected for conditioning the output signals of the Wheastone Bridge. This IC is an analog circuit that has a programmable amplifier and several offset compensation blocks that can be controlled digitally from a microcontroller. The analog-to-digital of the strain gauge signal conversion will be made on the microcontroller’s ADC. The sampling frequency has been estimated as near to 100-200 Hz taking into account the typical modes of vibration in aircraft’s structures.
Energy Harvesting. We have selected a thermal harvester as the source of additional energy in our system. Given the environmental conditions in which the system will operate we think that this source is the most readily available. The harvester circuitry has been designed to include the step-up converter and the battery charger. Power supply status indicators have also been included to measure the power provided by the harvester, battery fuel gauges and the power consumption of the sensor node.
Programming & Testing Circuitry. A serial interface and a JTAG connector have been added to the sensor node for testing and debugging purposes. Additionally we have included current sense circuitry to measure the power consumption of the sensor node under different modes of operation. The current sense is an analog circuit that is sampled by the A/D converter of the microcontroller.
• Global Node Architecture. The architecture of the global node has been divided into a coordinating node that has direct access to the Tx/Rx of the WSN and a computation node for post-processing the data obtained from the sensors. The block diagram is given in Figure 2. The main processor is an IMX51 Cortex-A8 ARM processor from Freescale. This device will hold a Linux OS that provides support for external devices like USB and micro-USB, SD card and ethernet connectivity. The processor interfaces with two elements of the global node: the WSN coordination node (see below) vi a SPI interface and the global computation element in a Spartan6 FPGA using the EIM (Extension Interface Module)
WSN Coordination Node. Its architecture is the same as other sensor node. The functionality is, of course, different providing network coordination and keeping synchronization with the rest of the sensor nodes. Their main task is to gather the data from the different sensors. The coordinating node has a SPI interface with the main processor (see next)
Global Computation. The computation node consists of an ARM processor (iMX51 @ 800MHz) and a FPGA (Spartan6 LX9) for hardware acceleration. The ARM processor obtains the data from the sensors via a SPI interface. Although the ARM device is capable of fast processing large amounts of data, the FPGA is serving for accelerating certain very demanding tasks. In our system the FPGA is currently performing two types of operations: a 1024-point FFT and 512-points cross-correlations.
- The processor handles the operation of the FPGA via a special memory interface that access to registers inside the FPGA to inform about the tasks that must be performed. That interface between processor and FPGA is made using very simple C code, so the operations in the FPGA are very transparent from the user point o view.
• Communications/Topology/Network Operation. The architecture of the wireless communication interface is based on the 802.15.4 standard in the 2.4GHz band. The chipsets that will be used in the sensor node are the CC2520 Transceiver and the MSP430 microcontroller, both from Texas Instrument. We have selected a dual-chip solution instead of a SoC solution because we wanted to have flexibility in the peripherals needed for the sensor, processing power and internal memory that a microcontroller has, as opposed to a single-chip solution that offers very limited performance. The network topology selected is a star-tree topology where each node communicates directly or through router nodes with the global node. The operation of the sensor network is such that each node obtains the measures from the sensors at the same time, but the data transmission is made sequentially one node at a time, so the whole bandwidth is available for the nodes, without additional interferences from other nodes. A node synchronization strategy must be followed in order to ensure the time-coherence of the data obtained from the sensors and the time-division operation of the wireless media.
Power Consumption and Battery Operation of the Sensor Nodes.
• Software Architecture. The proposed architecture is based on a multi-layered architecture with different software components. Low-level components (middleware) execute basic tasks, while higher level components use the API offered by the middleware to achieve more complicated functionality while maintaining efficiency and simplicity of coding. The basic functionality of our middleware system is to hide the low-level details of the sensor node (e.g. manage the system resources efficiently) by providing a clear interface to applications developed at the highest level.
o WSN Nodes. Sensor Node & Coordination Node
o Global Computation Processor.
• Testing and validation of the WSN
Based on these design decisions we have obtained the following results:
- A WSN consisting of several nodes. The WSN was demonstrated to work in a aircraft environment and work under different Duty-Cycle, different sensor options, sensing power state of the WSN (battery gauges), able to adapt to changing conditions in the RF links (power adaptation thanks to monitorization of RSSI values)
- A global computation node able to post-process data from the sensors and store data for further analysis. Large storage capability thanks to a SD card interface. External connection using Ethernet, easy and secure access thanks to ssh protocols.
- Analysis of functional specifications and requirements of the system in terms of bandwidth, data rate, frequency bands, power consumption and protocol stack to develop.
- Selection of a WSN architecture: protocol stack, frequency bands and configuration of the WSN
- Architecture of the sensor node: selection of components for the different sensors, the Tx/Rx and the software stack, energy harvesting and battery gauge circuitry. Methods for testing and measurements (serial link and power measurements)
- Architecture of the global node: selection of components, separation of global computation and WSN coordination, external interfaces with external infrastructure.
- Design of the Sensor Node schematic and layout, test plan for the sensor node, API functions for configuring the sensors and accessing the sensor data from the microcontroller. Development of software routines to measure the power consumption of the sensor node.
- Design of the Global Node schematic and layout, test plans for the global node, implement and embedded Linux in the global computation processor (ARM), communication between ARM and WSN coordinator (MSP430), global computation hardware in FPGA.
- Design of a Software Architecture for the WSN: data encapsulation and packing (data from the sensor, timestamp, RSSI, battery gauges), WSN configuration and Setup, WSN synchronization, WSN node coordination and adaptation.
- Design of Firmware for Sensor Node and for the coordinator node:
- Design of Global Computation Routines in the ARM processor: WSN Setup, SPI communication with coordinating node, Communication with the FPGA and hardware acceleration, FFT and cross-correlation, Post-processing data from Sensors, Lowpass filtering and decimation
- Test Review in HAI facilities in Nov’13 consisted in proofing the feasibility of the work made and the preparation of the WSN toward a more extensive demo scenario at the end of the project.
- Definition of a demonstration scenario at HAI facilities. Deployment of the nodes, coordination from the global node, sensor data post-processing in the global computation hardware (ARM+FPGA) and interface via Ethernet with an external application that is able to store and visualize the data from the different sensors at different node locations and modify the WSN operation parameters.
Potential Impact:
1. POTENTIAL IMPACT
To understand the potential impact of a research project like WILDCRAFT we have to look at how other people, normal citizens, visualize our work. In our relations with mass-media explaining the objectives of WIDLCRAFT we have had the opportunity to grasp the concerns and opportunities that a development like WILDCRAFT would represent for them.
The idea of WILDCRAFT is to provide the aircrafts with a set of fixed sensors that can be deployed around the aircrafts, take measures of certain physical aspects of the aircraft’s structure and forward those measures wirelessly to a central unit that provide time-coherence and perform complicated algorithms with those measures. The ultimate objective of WILDCRAFT would be to be able to extract the exact state of the aircraft structure from those algorithms with several consequences:
• Increased observability of parameters in the aircraft.
• Increased capacity to detect potential problems in the aircraft’s structure or nearby apparatus.
• Early detection of potential problems before they can be detected by normal periodic checks.
• Avoid/delay maintenance actions if no problems are detected.
• Because of the above, reduction of maintenance costs and other associated costs like aircraft down time.
• Potential reduction in cabling due to the wireless nature of the communications, which leads to less weight and fuel consumption and emissions.
• Increase the perception of safety from the users.
In general, the public still perceives safety as the most important concern regarding aircrafts. Despite the fact the aviation industry is the most secure transport media by a large distance, that safety regulations are extremely good and that they are greatly enforced by the aviation authorities, accidents still occur and have a profound impact in the society as a whole.
It is a fact that most of the people in developed countries have access to state-of-art technology in their hands (thanks to smart-phones and tablets): almost ubiquitous access to worldwide wireless communications, worldwide localization algorithms, sensoring health information (heart-rate, etc.) People are increasingly aware of those technologies and are continuously using them, but at the same time these technologies provide a false sense of instant availability. In this sense, we think there is an increasing perception from the users that technology is not being used at its best in the transportation sector. Therefore, there is a need to correct that perception by:
• More information and education to users and citizens about the limitations of technology and abou the process of adoption and deployment of technologies in safety critical activities.
• Information to the users and citizens about the costs associated with the final deployment of safety critical devices and services.
• Make the user of an aircraft aware that state-of-the-art technologies are being used in the aircraft and that this is increasing its own safety. Of course, to increase the perception of safety must not be compromising the safety itself.
In order to deploy WILDCRAFT we have designed a Roadmap that was described in D1.11. In this deliverable we discussed the more critical technologies that must be targeted in order to full deployment. A summary of the conclusions is given here and shown in Tables 1 and 2. Based on this analysis we have found the following technologies as the most demanding issues for system like WILDCRAFT (in yellow in above tables):
1. Data Fusion Algorithms:
o Multidisciplinary Research (mechanical, electronics, information theory, digital signal processing, aeronautics, etc)
o Support from the industry must see real and tangible benefits.
2. Battery Technology:
o Specify their batteries in the environment conditions that apply for aerospace.
o Specify battery charging/discharging behaviour with high and low temperatures.
o Establish appropriate airworthiness standards for Li-Ion battery installations and to ensure, as required by CS 25.601 that these battery installations do not have hazardous or unreliable design characteristics.
3. Co-existence with other wireless technologies. There is a strong need for these studies to be made and guarantee that a sufficient availability of the WILDCRAFT system is achieved while not hampering the operation of other services.
4. Network Synchronization: Network Time error between the nodes must be <50s.
5. Algorithm Robustness and Reliability: more efficient reliable methods should be considered, since the reliability has a cost in terms of resource usage, energy wastage, bandwidth consumption and effective data rate. Optimal solution will be found based on thoroughly testing in real environment.
A roadmap for a prototype of WILDCRAFT is given in attached document
2. EXPLOITATION OF FOREGROUND
The exploitable foreground declared in WILDCRAFT has the purpose of protecting hardware and software developments completed during the course of the project.
CEIT has declared foreground of hardware devices (which includes schematics and layout) related to sensor and global nodes. The functionalities that that hardware is implementing are: wireless communications (Zigbee based RF transceiver and microcontroller), power management for harvesting and storage, strain gage sensor conditioning circuitry and accompanying software modules for configuring and controlling the sensor devices.
The purpose of the declared foreground is to leverage the know-how gained during the project to support other industrial activities that can make use of similar technologies such as WSN.
As a Research Institution the commercial exploitation of this foreground will be done mainly via:
• Research Projects with interested companies in sectors like energy (smart grids, maintenance systems), civil engineering (structural health monitoring based WSN) or automotive.
• Creation of spin-off companies that can commercialize not only the foreground but at the same time provides specific services for customers in the above mentioned sectors.
Currently CEIT is participating in projects in collaboration with local industries (energy sector) in which the foreground declared here will be applied.
INTE declared foreground of software modules running in microcontroller devices. The functionalities provided are power management strategies for WSN, WSN Topology management and synchronization, automatic power transmission control, communication between ARM and MSP430 and tester applications for management and configuration of the WSN. INTE is a software company that offers specific solutions for satellite operators and installers: carrier spectrum monitoring, demodulation under carrier interference, automated calibration etc. Additionally Integrasys has already implemented WSN for monitoring plant factory for civil engineering. The purpose of the foreground presented by Integrasys is to diversify the activities of the company and targeting other sectors related to communications but in the topic of the smart grids and maintenance systems in general. In these areas WSN represent a good opportunity to increase and enhance the portfolio of products and services that Integrasys currently holds. The activities of Integrasys towards achieving these objectives involve a continuous presence in panels and committees at the European level promoting the use of embedded systems.
The additional research needed must accommodate the current foreground declared to the specific conditions of the sector: electrical specifications (power consumption requirements), functional specifications (type of sensors require), communications (bandwidth, frequency bands, latency, data rate, etc). A detailed analysis of needed further research has been detailed in deliverable D1.11. In that document we used two indicators:
• The Enabling Factor Rank (EFR) is the importance of that technology in the deployment of WILDCRAFT. The lower this number is, the more important it is.
• The estimated Time Frame (TF) at which a solution will be found
As a result, we calculated the Priority Rank as the relation between the Time Frame and the Enabling Factor Rank (TF/EFR). This number tells us the priority of the technology in question. The summarized results are illustrated in the tables shown in attached document (more information can be seen in D1.11)
The tables below show the main dissemination activities in the media during the project.
In general, the mass media has shown a great interest in the results of WILDCRAFT. We have participated live in nationwide and regional programs (TV and radio) explaining the objectives of WILDCRAFT, showing our sensor nodes and how this can be used to improve the safety of aircrafts. Furthermore, the spanish digital newspapers elconfidencial.com published a report about WILDCRAFT and also the bbc.co.uk showed an interest in our work.
The link to all the published material (audio, video, etc) can be found in the tables given in the attached document.
WILDCRAFT was also presented to the Joint Technical Committee ISO/IEC JTC 1/WG7 on Sensor Networks (WGSN). The committee is formed by a number of experts from companies all around the world interested in the definition of protocols and techniques for WSN.
The partners have submitted a paper to the XXIX Conference on Design of Circuits and Integrated Systems (DCIS’14). The title of the paper is “Design Principles and Challenges for an Autonomous WSN for Structural Health Monitoring in Aircrafts”.
List of Websites:
http://www.wildcraft-eu.org/
Andoni Irizar, airizar@ceit.es
