Recipient Organization
UNIVERSAL SCHEDULE AND BOOKING LLC
701 WASHINGTON ST
HARPERS FERRY,WV 254256998
Performing Department
(N/A)
Non Technical Summary
Rural communities face compounding challenges with the impacts to labor, health, and economic from the opioid crisis, the coronavirus pandemic, and now mounting pressures to reach greenhouse gas (GHG) reductions to mitigate climate change. The recent Renewable Energy for America Program as part of the Congressional Inflation Reduction Act provided a vital downpayment on the resources needed to incentivize rural businesses and communities to implement the activities needed to reach GHG goals. However, the rate of change, scale, and complexities involved with highly varied residential and commercial building inventories is a very big challenge. This Phase I R&D proposal from Universal Schedule and Booking (USB) seeks to determine feasibility for machine learning to correlate energy, efficiency, and emissions profiles for these buildings on building-by-building bases, without the need for widespread installation of new sensors. Sensors are often cost prohibitive, have technical challenges for rural populations, and introduce cybersecurity risks. The research activities include proprietary digital infrastructure to facilitate a shift in economic framework for rural communities, so that the drive to reach net-zero GHG goals by 2030, 2040, 2050 becomes primarily an economic opportunity for rural communities and governments. In collaboration with Texas A&M University Mechanical Engineering Department, the results of this SBIR/STTR research will assist USDAwith reaching Federal GHG reduction goals and aligns with National Institute of Food and Agricultural Topic 8.6 Research Priorities for development of technologies that protect or enhance the environment and address climate change while promoting economicdevelopment.
Animal Health Component
50%
Research Effort Categories
Basic
25%
Applied
50%
Developmental
25%
Goals / Objectives
Greenhouse Gas (GHG) emissions are linked to negative agricultural, health, and environmental impacts. Rural America has a unique opportunity to reach the White House's carbon net-zero (CNZ) goals by 2030, 2040, and 2050 [1]. However, economic challenges, poverty, health epidemics, and climate change stand in the way. Driving reductions to GHG, set within a framework to achieve economic development, has the potential to simultaneously reduce negative impacts to health, enhance the environment, and address the socioeconomic challenges facing families and rural communities [2].The problem is that the digital infrastructure is lacking. Existing digital infrastructures, namely for communication and commerce, have been dominated by popular social media and search engines to generate profits with ratings-based advertising business models rather than enabling market-driven forces to align with economic development and achieve sustainable development goals--placing excess burden on communities and state/local governments/taxpayers to mitigate the problem. For example eroding advertising revenues increasingly forces local newspapers to close, which fractures communities who lack balanced journalistic reporting [3]. Other negative impacts are the mounting evidence of social isolation, mental health issues, and lost economic opportunity [4-8]. Federal data privacy regulations are limit internet-based tracking devices used to generate ~$1,610bn in revenue for these companies since 2010 [9-10]. The regulations create a vital opportunity for tech that is developed and deployed to address rural economic development.With patented and patent-pending technology, Universal Schedule and Booking (USB) proposes R&D for machine learning to power a software-as-a-service (SaaS) model to drive rural economic development while simultaneously protecting the environment and addressing climate change.The goal of this Phase I study is to determine the feasibility of a rural community-level stakeholder platform software interface to an incentive/reward/subsidy payment system to drive building decarbonization for rural communities with low-tech and/or high-tech software application (app) accesspoints.
Project Methods
Determine modeling software and efficiency variables needed to generate a sufficient proof of concept that the ML algorithm is feasible.Determine end-user and community requirements for designing the smart digital infrastructure to facilitate community-driven agency and participation while providing policymakers, governments, and scientists the data needed to drive decarbonization for buildings.Determine the system design requirements for the end-users and stakeholders to enable community-driven decision-making to deploy incentives to households that drive building decarbonization.