A platform for ubiquitous sensor deployment in occupational and domestic environments

Lifton, Joshua; Feldmeier, Mark; Ono, Yasuhiro; Lewis, Cameron; Paradiso, Joseph A.

doi:10.1145/1236360.1236377

Cited by 80 publications

(33 citation statements)

References 15 publications

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“…Monitoring building energy consumption is an important opportunity for savings in an increasingly energy-conscious era; in fact, many AC power metering and control devices already exist and some are even network-enabled [28,13]. However, since these are either commercially unavailable or cost prohibitive, we developed a platform for AC power metering, seen in Figure 7(b), to support research in energyaware decision-making in datacenter and home environments both inexpensively and at scale.…”

Section: Ac Power Monitoringmentioning

confidence: 99%

A building block approach to sensornet systems

Dutta

Taneja

Jeong

et al. 2008

Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems

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We present a building block approach to hardware platform design based on a decade of collective experience in this area, arriving at an architecture in which general-purpose modules that require expertise to design and incorporate commonlyused functionality are integrated with application-specific carriers that satisfy the unique sensing, power supply, and mechanical constraints of an application. Of course, modules are widespread, but our focus is far less on the performance of any individual module and far more on an overall architecture that supports the prototype, pilot, and production stages of design, and preserves the artifacts and learnings accumulated along the way.We present heuristics for partitioning functionality between modules and carriers, and identify guidelines for their interconnection. Our approach advocates exporting a wide electrical interface, eliminating the system bus, and supporting many physical interconnect options for modules and carriers. We evaluate this approach by constructing a family of general-purpose modules and application-specific carriers that achieve a high degree of reuse despite very different application requirements. We show that this approach shortens platform development time-to-result for novice graduate students, making custom platforms broadly accessible.

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Section: Ac Power Monitoringmentioning

confidence: 99%

A building block approach to sensornet systems

Dutta

Taneja

Jeong

et al. 2008

Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems

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“…Despite the higher installation efforts, these distributed sensors can both be utilized to identify as well as control the connected appliance. The Plug [16], the ACme platform [17] and the Plugwise [5] are examples of such direct distributed sensing platforms, which monitor the power consumption of the plugged-in appliance. An identification of the attached loads is however unsupported by these platforms, despite the fact that they employ microcontrollers which can be programmed to locally process collected readings.…”

Section: Related Workmentioning

confidence: 99%

Electric appliance classification based on distributed high resolution current sensing

Reinhardt

Burkhardt

Zaheer

et al. 2012

37th Annual IEEE Conference on Local Computer Networks -- Workshops

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Today's solutions to inform residents about their electricity consumption are mostly confined to displaying aggregate readings collected at meter level. A reliable identification of appliances that require disproportionate amounts of energy for their operation is generally unsupported by these systems, or at least requires significant manual configuration efforts. We address this challenge by placing low-cost measurement and actuation units into the mains connection of appliances. The distributed sensors capture the current flow of individual appliances at a sampling rate of 1.6kHz and apply local signal processing to the readings in order to extract characteristic fingerprints. These fingerprints are communicated wirelessly to the evaluation server, thus keeping the required airtime and energy demand of the transmission low. The evaluation server employs machine learning techniques and caters for the actual classification of attached electric appliances based on their fingerprints, enabling the correlation of consumption data and the appliance identity. Our evaluation is based on more than 3,000 current consumption fingerprints, which we have captured for a range of household appliances. The results indicate that a high accuracy is achieved when locally extracted current consumption fingerprints are used to classify appliances.

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“…The MIT Plug [1] provided users with power and sensor information by means of a smart surge protector. In [2], the author's present experiences using the ACme wireless plug sensor in an office environment.…”

Section: Related Workmentioning

confidence: 99%

Contactless sensing of appliance state transitions through variations in electromagnetic fields

Rowe

Bergés

Rajkumar

2010

Proceedings of the 2nd ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Building

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Non-Intrusive Load Monitoring (NILM) is a promising technique for disaggregating per-appliance energy consumption in buildings from aggregate voltage/current measurements. One major limitation of the approach is that it typically requires a training phase during which users must manually label device transitions. In this paper, we present an inexpensive contactless electromagnetic field (EMF) event-detector that can detect appliance state changes within close proximity based on magnetic and electric field fluctuations. Each detector wirelessly transmits state changes to a circuit-panel energy meter, which can then be used to label and disambiguate appliance transitions detected from the aggregate signals as well as to track the associated energy consumption. Our EMF sensors are able to detect significant power state changes from a few inches away making it possible to externally monitor in-wall wiring to devices (e.g., overhead lights). We experimentally evaluate our proposed EMF sensor in terms of power consumption, accuracy and detection range on a variety of appliances to demonstrate its effectiveness towards augmenting NILM systems. We show that accurately detecting 100W loads from 10cm away is possible while maintaining multiple-year battery life from a coin-cell battery.

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A platform for ubiquitous sensor deployment in occupational and domestic environments

Cited by 80 publications

References 15 publications

A building block approach to sensornet systems

A building block approach to sensornet systems

Electric appliance classification based on distributed high resolution current sensing

Contactless sensing of appliance state transitions through variations in electromagnetic fields

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