A Distributed Energy Monitoring and Analytics Platform and its Use Cases

Klingensmith, Neil; Willis, Dale; Banerjee, Suman

doi:10.1145/2528282.2528283

Cited by 18 publications

(6 citation statements)

References 10 publications

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“…Panel level meters [20,24] provide reasonable sensing insight while only having to be installed in panel boxes and not at every load. However, meters that use a direct connection to a spare breaker to power themselves typically require an electrician to install, raising installation costs.…”

Section: Energy Consumptionmentioning

confidence: 99%

An energy-harvesting sensor architecture and toolkit for building monitoring and event detection

Campbell

Dutta

2014

Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings

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Understanding building usage patterns and resource consumption, particularly for existing buildings, requires a sensing infrastructure for the building. Often, deploying these sensors and obtaining real-time information is hindered by installation and maintenance difficulties resulting from scaling down and powering these devices. Devices that rely on batteries are limited by the scale of the batteries and the maintenance cost of replacing them while AC mains powered sensors incur high upfront installation costs. To mitigate these burdens, we present a new architecture for designing building-monitoring focused energy-harvesting sensors.The key to this architecture is masking the inevitable intermittency provided by energy-harvesting with a trigger abstraction that activates the device only when there is useful work to be done. In this paper, we describe our architecture and demonstrate how it supports existing energy-harvesting sensor designs. Further, we realize three additional design points within the architecture and demonstrate how the sensors are effective at building monitoring and event detection. The sensors, however, are classically disruptive: they improve ease of installation and maintenance, but to do so, they sacrifice some fidelity and reliability. Whether this tradeoff is acceptable remains to be explored, but the technology needed to do so is now here.

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Section: Energy Consumptionmentioning

confidence: 99%

An energy-harvesting sensor architecture and toolkit for building monitoring and event detection

Campbell

Dutta

2014

Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings

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“…Each of these services contain a fully implemented set of applications to capture, process, store, and visualize the data from their wireless sensors within a virtually isolated environment. The first service is a wireless environmental sensor designed as part of the Emonix research platform [4], which we refer to as "EnvSense". The second service is a wireless security camera based on a commercially available D-Link 931L webcam, which we call "SecCams".…”

Section: Paradrop Capabilitiesmentioning

confidence: 99%

ParaDrop

Willis

Dasgupta

Banerjee

2014

Proceedings of the 9th ACM Workshop on Mobility in the Evolving Internet Architecture

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The landscape of computing capabilities within the home has seen a recent shift from persistent desktops to mobile platforms, which has led to the use of the cloud as the primary computing platform implemented by developers today. However, a growing number of high quality services restrict computational tasks to be colocated with the enduser. Thus, we introduce a specific edge computing framework, called ParaDrop, which allows developers to leverage one of the last bastions of persistent computing resources in the end customer premises: the gateway (e.g., the WiFi Access Point or home set-top box). Using our platform, which has been fully implemented on real hardware, developers can design virtually isolated compute containers to provide an persistent computational presence in the proximity of the end-user. The compute containers, retain user state, and also move with the users as the latter changes their points of attachment. We demonstrate the capabilities of our platform by implementing two third-party applications, which utilize the framework we have provided. The framework we have implemented for the developer allows multitenancy through virtualization, dynamic installation through our developer API, and tight resource control through a managed policy design.

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“…Commercial water softeners do not track this data or make it available to users. Figure 1 shows a diagram of the data flow used to collect data from Emonix H 2 O sensors, which are based on the Emonix platform, an embedded platform originally designed by our lab to measure energy consumption [3].…”

Section: Online Monitoringmentioning

confidence: 99%

Water or slime? A platform for automating water treatment systems

Klingensmith¹,

Chulick²,

Bomber³

et al. 2014

Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings

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Worldwide, the availability of water is increasingly becoming a political and environmental concern. With a quarter of the world's population living downstream of the receding Himalayan glaciers [1], tensions over availability of fresh water supplies will only rise in the coming years. Surprisingly, few technical solutions have arisen to rein in wasteful water consumption or pollution. In fact, society has a poor understanding about the causes of wasteful consumption and pollution patterns at the heart of these concerns. With Emonix H 2 O, we aim to provide a platform for municipalities in developing and developed regions to identify and control sources of waste in water distribution and treatment systems. Emonix H 2 O provides users with a high-level understanding about water consumption patterns by tracking flow rate and water quality across multiple locations in real time. In a pilot deployment, we demonstrate that simply making system maintainers aware of malfunctions in treatment equipment can drastically reduce waste and pollution.

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A Distributed Energy Monitoring and Analytics Platform and its Use Cases

Cited by 18 publications

References 10 publications

An energy-harvesting sensor architecture and toolkit for building monitoring and event detection

An energy-harvesting sensor architecture and toolkit for building monitoring and event detection

ParaDrop

Water or slime? A platform for automating water treatment systems

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