SBIR/STTR Research Award

SBIR Phase I: Virtual Fences for Sustainable Protection

Award identifier 7e1adc46330ca8feee6a9f1c8fac5c4d26d2a0e38fc830080394495efd19ea37Awarding agency National Science Foundation

Award amount

$224,963

Program and phase

SBIR · Phase I

Award year

2017

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
Samraksh Company, The
Proposal award date
2016-12-15
Contract end date
2017-08-31
UEI
UPF6E14LPMK7
Solicitation number
Not reported
Topic code
IT

Research abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project comes from addressing a demand in many parts of the world for a scalable technological solution for managers of nature resources to deal with human-animal conflicts and rapid deforestation. Natural resources have large and sometimes surprising ecosystem impact. Even the direct economic value of individual wildlife and forest reserves is often in the hundreds of millions of dollars. Operationally relevant protection technologies that are sustainable can serve as an import tool in effective management. Having a low total cost of ownership and effectively co-existing with conventional human surveillance methods is key to sustainability. We seek to commercialize a protection system that is sustainable as it offers low cost, long lived devices, ease of use and maintenance, robust performance across diverse natural environments, and stealthy operation. It also augments accountability of the guards, and automates tasks such as notifying management and sharing forensic evidence of incidents in settings where communication infrastructure is not readily available. The proposed project addresses the challenge with reducing energy consumption for our battery powered, radar device based, mesh network solution for persistent, time-sensitive protection of natural resources. Commercial impact for the proposed system can only be realized if the sensor is low-power, the data driven machine learning based signal processing is low-power, and the wide area networking is low-power. Addressing all these will unlock commercial value, but the impact is limited by the least efficient part of the system. Today the radar's efficiency is the essential bottleneck in system performance; it consumes about 40 milliWatts (mW). Reducing the radar's consumption to 5mW would double, and reducing it to 1mW would at least triple, the time between battery changes. The proposed effort would design, implement, and validate power reduction in the radar subsystem and integrate the result into an overall system. The largest technical risk in the plan is the Radio Frequency subsystem, which will therefore be addressed in Phase I. Phase II will implement power reductions in all the other radar subsystems, integrate the results into a coherent sensor, and integrate that sensor into the overall system. This integration into the larger system will also deal with whole system optimizations.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

9 SBIR/STTR records share this UEI (2009–2020). Reported award amounts total $3,387,592. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, Department of Energy, National Science Foundation

Agency intelligence

National Science Foundation

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