Demo: Snap – Rapid Sensornet Deployment with a Sensornet Appstore

Despite ease of deployment being seen as a primary advantage of sensor networks, deployment remains difficult. We present Snap, a system for rapid sensornet deployment that allows sensor networks to be deployed, positioned, and reprogrammed through a sensornet appstore. Snap uses a smartphone interface that uses QR codes for node identification, a map interface for node positioning, and dynamic loading of applications on the nodes. Snap nodes run the Contiki operating system and its low-power IPv6 network stack that provides direct access from nodes to the smartphone application. We demonstrate rapid sensor node deployment, identification, positioning, and node reprogramming within seconds, over a multi-hop sensornet routing path with a WiFi-connected smartphone

Spray, Embracing Multimodality

We present Spray, a localization system that compensates for low accuracy of individual localization measurements by combining measurements from multiple localization modalities

Multi-Channel Two-way Time of Flight Sensor Network Ranging

Two-way time of flight (ToF) ranging is one of the most interesting approaches for localization in wireless sensor networking since previous ToF ranging approaches using commercial off-the-shelf (COTS) devices have achieved good accuracy. The COTS-based approaches were, however, evaluated only in line-of-sight conditions. In this paper, we extend ToF ranging using multiple IEEE 802.15.4 channels. Our results demonstrate that with multiple channels we can achieve good accuracy even in non line-of-sight conditions. Furthermore, our measurements suggest that the variance between different channels serves as a good estimate of the accuracy of the measurements, which can be valuable information for applications that require localization information

StrawMAN: Making Sudden Traffic Surges Graceful in Low-Power Wireless Networks

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Inspirational Bits - Towards a Shared Understanding of the Digital Material

In any design process, a medium’s properties need to be considered. This is nothing new in design. Still we find that in HCI and interactive systems design the properties of a technology are often glossed over. That is, technologies are black-boxed without much thought given to how their distinctive properties open up design possibilities. In this paper we describe what we call inspirational bits as a way to become more familiar with the design material in HCI, the digital material. We describe inspirational bits as quick and dirty but fully working systems in both hardware and software built with the aim of exposing one or several of the dynamic properties of a digital material. We also show how they provide a means of sharing design knowledge across the members of a multi-disciplined design team

Leveraging IP for Sensor Network Deployment

Ease of deployment has always been seen as a major selling point of wireless sensor networks, yet experience has shown deployment to be difficult. We argue that parts of these difficulties have come from the lack of a generic networking layer and of well-tested, generic transport protocols in traditional sensornet deployments. We believe that the use of low-power IPv6 can help by providing nodelevel addressing, point-to-point routing, and generic well-tested transport protocols. We evaluate the performance of HTTP/TCP and CoAP/UDP over a duty cycled radio layer, showing that with a small modification to the duty cycling layer results in a dramatic improvement in performance at a retained low power consumption. Based on our experiences, we introduce an in-network caching mechanism that significantly improves the performance of software updates in incrementally deployed sensor networks. Our results are the first steps towards a deployment tool for IP-based sensor networks. 1

Safety positioning for first responders to fires in underground constructions: A pre-study of demands and possibilities

This report presents the results of the SafePos pre-study, in which different technologies for safety positioning to be used by first responders were identified, and techniques for ad hoc positioning were evaluated. The aim of the project, was to test various systems for localisation and communication and narrow- and wide-band radio transmission techniques, and to further investigate how the presence of such a system could support fire and rescue operations in complex underground environments. Tests have been carried out in real, pre-existing mining environments, and complex office corridors with similar conditions to those of a mine as regards curves and obstructions have been used for introductory tests. A computer application for digital simulation has been developed and adapted to the system, although this only operates on a relatively basic level, so as to support the testing of the positioning and communication systems; thus, more can be done to improve performance for real-life applications. The analysis was conducted by studying the results of the experiments and linking them to expected usage during a fire and rescue operation. Tests have also been carried out in cooperation with the fire and rescue services in order to identify equipment and wearable technologies that could support and make fire and rescue operations in mines and other complex underground constructions safer and more efficient. In order to transfer information to and from these wearable technologies and to improve the likelihood of a safe and efficient fire and rescue operation, positioning and connectivity are requirements.Keywords: Underground constructions, mine, fire safety, positioning, connectivit

Smart condition assessment, surveillance and management of critical bridges

Bridges with known deficiencies often have to be kept in service as they constitute links in highly stressed transport infrastructures. Disruptions in the traffic flow are often considered unacceptable. The current project was aimed at bridges with known deficiencies in particular, with the purpose of securing the serviceability and the safety using an innovative smart system for surveillance and condition assessment. Related to measurements and collection of data, the project has focused on wireless sensor networks. In comparison to traditional wired systems, the installation demands less resources and the locations of the sensor nodes are not restricted by cabling issues. The research activities regarding sensors have been aimed at energy harvesting and energy efficient scheduling of operations. A completely wireless installation requires local power sources as batteries with limited lifetime, which restricts the time for measurements. With the purpose of extending the lifetime, systems for energy harvesting have been evaluated as, e.g., units based on vibrations and electromagnetic waves. Another aspect is when and for how long measurements and communication should be performed. By scheduling the activities of the sensor node, the results of the project shows a potential to save energy. The purpose of a monitoring system is to provide data for condition assessment and damage detection. A condition assessment involves the estimation of the present safety level and a prediction of the remaining service life. Within this field, degradation models for the interaction between corrosion and fatigue have been studied, and a probabilistic model have been developed facilitating considerations of uncertainties in the measured response and in the results from inspections. The purpose of damage detection is to find anomalies in the behaviour of the structure that might be caused by damages or a change in structural behaviour. It can involve unexpected events difficult to predict in advance, but detectable by thorough investigation of measured data. A method based on machine learning and statistical inference have been developed in the project and tested on fictitious damage cases. If the results form a condition assessment or damage detection indicates insufficient safety, a decision has to be made on interventions. A decision support model based on Bayesian decision theory have been implemented in the project and tested on data from the Old Lidingö Bridge. Cloud based services have been developed to transfer data from the sensors, to the analysis parts, and on to the decision agent. The purpose was to simplify the management of large data volumes from a monitoring system and to visualize the results in a comprehensible format. Solutions for collecting, storing and sharing of data have been developed, together with a mobile app for presentation of the results. The objective to develop an integrated system for surveillance, sharing of data, condition assessment, and decision support is partly completed. Some parts of the integration remains to be solved before a complete solution can be launched.QC 20190515</p

Smart condition assessment, surveillance and management of critical bridges

Bridges with known deficiencies often have to be kept in service as they constitute links in highly stressed transport infrastructures. Disruptions in the traffic flow are often considered unacceptable. The current project was aimed at bridges with known deficiencies in particular, with the purpose of securing the serviceability and the safety using an innovative smart system for surveillance and condition assessment. Related to measurements and collection of data, the project has focused on wireless sensor networks. In comparison to traditional wired systems, the installation demands less resources and the locations of the sensor nodes are not restricted by cabling issues. The research activities regarding sensors have been aimed at energy harvesting and energy efficient scheduling of operations. A completely wireless installation requires local power sources as batteries with limited lifetime, which restricts the time for measurements. With the purpose of extending the lifetime, systems for energy harvesting have been evaluated as, e.g., units based on vibrations and electromagnetic waves. Another aspect is when and for how long measurements and communication should be performed. By scheduling the activities of the sensor node, the results of the project shows a potential to save energy. The purpose of a monitoring system is to provide data for condition assessment and damage detection. A condition assessment involves the estimation of the present safety level and a prediction of the remaining service life. Within this field, degradation models for the interaction between corrosion and fatigue have been studied, and a probabilistic model have been developed facilitating considerations of uncertainties in the measured response and in the results from inspections. The purpose of damage detection is to find anomalies in the behaviour of the structure that might be caused by damages or a change in structural behaviour. It can involve unexpected events difficult to predict in advance, but detectable by thorough investigation of measured data. A method based on machine learning and statistical inference have been developed in the project and tested on fictitious damage cases. If the results form a condition assessment or damage detection indicates insufficient safety, a decision has to be made on interventions. A decision support model based on Bayesian decision theory have been implemented in the project and tested on data from the Old Lidingö Bridge. Cloud based services have been developed to transfer data from the sensors, to the analysis parts, and on to the decision agent. The purpose was to simplify the management of large data volumes from a monitoring system and to visualize the results in a comprehensible format. Solutions for collecting, storing and sharing of data have been developed, together with a mobile app for presentation of the results. The objective to develop an integrated system for surveillance, sharing of data, condition assessment, and decision support is partly completed. Some parts of the integration remains to be solved before a complete solution can be launched.QC 20190515</p

Smart condition assessment, surveillance and management of critical bridges

Bridges with known deficiencies often have to be kept in service as they constitute links in highly stressed transport infrastructures. Disruptions in the traffic flow are often considered unacceptable. The current project was aimed at bridges with known deficiencies in particular, with the purpose of securing the serviceability and the safety using an innovative smart system for surveillance and condition assessment. Related to measurements and collection of data, the project has focused on wireless sensor networks. In comparison to traditional wired systems, the installation demands less resources and the locations of the sensor nodes are not restricted by cabling issues. The research activities regarding sensors have been aimed at energy harvesting and energy efficient scheduling of operations. A completely wireless installation requires local power sources as batteries with limited lifetime, which restricts the time for measurements. With the purpose of extending the lifetime, systems for energy harvesting have been evaluated as, e.g., units based on vibrations and electromagnetic waves. Another aspect is when and for how long measurements and communication should be performed. By scheduling the activities of the sensor node, the results of the project shows a potential to save energy. The purpose of a monitoring system is to provide data for condition assessment and damage detection. A condition assessment involves the estimation of the present safety level and a prediction of the remaining service life. Within this field, degradation models for the interaction between corrosion and fatigue have been studied, and a probabilistic model have been developed facilitating considerations of uncertainties in the measured response and in the results from inspections. The purpose of damage detection is to find anomalies in the behaviour of the structure that might be caused by damages or a change in structural behaviour. It can involve unexpected events difficult to predict in advance, but detectable by thorough investigation of measured data. A method based on machine learning and statistical inference have been developed in the project and tested on fictitious damage cases. If the results form a condition assessment or damage detection indicates insufficient safety, a decision has to be made on interventions. A decision support model based on Bayesian decision theory have been implemented in the project and tested on data from the Old Lidingö Bridge. Cloud based services have been developed to transfer data from the sensors, to the analysis parts, and on to the decision agent. The purpose was to simplify the management of large data volumes from a monitoring system and to visualize the results in a comprehensible format. Solutions for collecting, storing and sharing of data have been developed, together with a mobile app for presentation of the results. The objective to develop an integrated system for surveillance, sharing of data, condition assessment, and decision support is partly completed. Some parts of the integration remains to be solved before a complete solution can be launched.QC 20190515</p