Prototyping Wireless Sensor Network Applications with BTnodes

Beutel, Jan; Kasten, Oliver; Mattern, Friedemann; Römer, Kay Uwe; Siegemund, Frank; Thiele, Lothar

doi:10.1007/978-3-540-24606-0_22

Cited by 84 publications

(46 citation statements)

References 21 publications

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“…Currently, many of the systems used for collecting environmental parameters are based on sensor network nodes which are located in a specific local regions that transfer data to a central database (iMotes [6], ECOs [11] and BTnodes [1]). The large scale of deployment and their price requirements imply that resources in terms of energy, memory, computational speed and bandwidth are severely constrained.…”

Section: Environmental Monitoringmentioning

confidence: 99%

MobGeoSen: facilitating personal geosensor data collection and visualization using mobile phones

Kanjo

Benford

Paxton

et al. 2007

Pers Ubiquit Comput

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Mobile sensing and mapping applications are becoming more prevalent because sensing hardware is becoming more portable and more affordable. However, most of the hardware uses small numbers of fixed sensors that report and share multiple sets of environmental data which raises privacy concerns. Instead, these systems can be decentralized and managed by individuals in their public and private spaces. This paper describes a robust system called MobGeoSens which enables individuals to monitor their local environment (e.g. pollution and temperature) and their private spaces (e.g. activities and health) by using mobile phones in their day to day life.The MobGeoSen is a combination of software components that facilitates the phone's internal sensing devices (e.g. microphone and camera) and external wireless sensors (e.g. data loggers and GPS receivers) for data collection. It also adds a new dimension of spatial localization to the data collection process and provides the user with both textual and spatial cartographic displays. While collecting the data, individuals can interactively add annotations and photos which are automatically added and integrated in the visualization file/log. This makes it easy to visualize the data, photos and annotations on a spatial and temporal visualization tool. In addition, the paper will present ways in which mobile phones can be used as noise sensors using an on-device microphone. Finally, we present our experiences with school children using the above mentioned system to measure their exposure to environmental pollution.

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Section: Environmental Monitoringmentioning

confidence: 99%

MobGeoSen: facilitating personal geosensor data collection and visualization using mobile phones

Kanjo

Benford

Paxton

et al. 2007

Pers Ubiquit Comput

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“…However, the application of this research is largely focussed on utilising data collected from communication between numerous (highly resource constrained) nodes to monitor an environment. While the application of sensor nodes may differ in WSNs several examples of hardware platform used (such as BTnodes [18]) are similar to that used in this work.…”

Section: Discussion and Future Workmentioning

confidence: 99%

Exploring the Design of Pay-Per-Use Objects in the Construction Domain

Fitton

Sundramoorthy

Kortuem

et al. 2008

Lecture Notes in Computer Science

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Abstract. Equipment used in the construction domain is often hired in order to reduce cost and maintenance overhead. The cost of hire is dependent on the time period involved and does not take into account the actual use equipment has received. This paper presents our initial investigation into how physical objects augmented with sensing and communication technologies can measure use in order to enable new pay-per-use payment models for equipment hire. We also explore user interaction with pay-per-use objects via mobile devices. The user interactions that take place within our prototype scenario range from simple information access to transactions involving multiple users. This paper presents the design, implementation and evaluation of a prototype pay-per-use system motivated by a real world equipment hire scenario. We also provide insights into the various challenges introduced by supporting a pay-per-use model, including data storage and data security in addition to user interaction issues.

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“…Few sensor network testbeds measure the energy consumption of their nodes, and those who do are limited: In the MoteLab testbed [6] for example, only one sensor node is being measured. The JAWS testbed [7] supports energy measurement capabilities for all sensor nodes using BTnodes [8] for the monitoring network [9]. However, measurement accuracy and detail are limited by the sensor nodes' internal analog digital converter (ADC) and by the bluetooth monitoring network, respectively.…”

Section: Related Workmentioning

confidence: 99%

Towards a Realistic Energy Model for Wireless Sensor Networks

Kellner¹,

Pink²,

Meier³

et al. 2008

2008 Fifth Annual Conference on Wireless on Demand Network Systems and Services

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Abstract-Energy consumption is one of the most critical protocol properties in a wireless sensor network. Therefore, a precise energy model is required for the evaluation of protocols. In addition to evaluation, an energy model can also be used for on-line energy accounting. After processing user queries, nodes aware of the energy model can send an energy bill towards the network's data sink. This allows the user to adjust future queries to be more energy efficient. The contribution of this paper is twofold: First, a theoretical energy model based on simple finite automata is presented. This model can be used for online accounting, simulation and generation of a-priori knowledge. Second, the proposed theoretical model is backed up by practical measurements using a new measurement device called SNMD, which also offers management functions for sensor-net testbeds. Therewith, output of the theoretical model can be compared to and validated against by real-world measurements.

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Prototyping Wireless Sensor Network Applications with BTnodes

Cited by 84 publications

References 21 publications

MobGeoSen: facilitating personal geosensor data collection and visualization using mobile phones

MobGeoSen: facilitating personal geosensor data collection and visualization using mobile phones

Exploring the Design of Pay-Per-Use Objects in the Construction Domain

Towards a Realistic Energy Model for Wireless Sensor Networks

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