Progress 09/01/23 to 08/31/24
Outputs
Target Audience:LATERAL.systems' (LATERAL) target audience, or key target market, for our Controlled Environment Agriculture (CEA), indoor, water quality and atmospheric conditions monitoring platform are indoor commercial farmers. In particular, our primary target audience are hydroponics and aquaponics farmers. LATERAL is engineering our technology in close concert with what CEA farm owners and managers tell us that they want and need to improve efficiencies. We have now conducted over 400 customer discovery interviews to gain a broad perspective on farmers' needs. In addition to farmers, LATERAL is conducting customer discovery interviews with agricultural distributors and retailers, agricultural consultants and extension agents, and faculty involved CEA workforce development training programs at universities and community colleges as well as non-profit program instructors. For example, LATERAL attended the Indoor Ag Con on March 11-12, 2024 where we conducted nearly 100 interviews with conference attendees. Many of these interviews led to warm introductions with additional indoor farming stakeholders leading to additional customer discovery interviews. Changes/Problems:No major changes or problem have occurred. LATERAL is on track with the overall project timelines with the exception of slight adjustments to the field-testing plan and timeline. Oregon State University experienced a delay in replacing their water pump system and the university IACUC board will not approve keeping fish in the aquaponics system at NWREC until the pump system is replaced. Therefore, LATERAL recently decided to move forward with field testing in just the hydroponics systems at NWREC and not involve the aquaponics system. This revision will still accomplish the grant objectives since we can continue experiments in the aquaponics system in the lab while moving forward with testing in two hydroponics systems the greenhouse at NWREC. What opportunities for training and professional development has the project provided?We view SBIR funding as an excellent opportunity to vet and train engineers for consideration for full employment when our company launches to revenue. In keeping with that goal, we have made significant progress coalescing and training a team of four highly dedicated and skilled engineers. We have also contracted with a highly experienced technical marketing strategist who is mentoring our business development intern, a second-year NYU Stern School of Business student involved in the Endless Frontier Labs business accelerator program LATERAL is participating in now (September, 2024 through June of 2025). This particular grant effort is focused on engineering R&D rather than STEM education; however, we are indeed laying track for future training and professional development programming. For example, we have a strong relationship with Oregon State University (OSU), a land grant institution that serves seven Oregon counties and operates as a hub where nearly 40% of the total farmgate value of Oregon agriculture generated within a 50-mile radius. We gifted one of our aquaponics systems to the OSU North Willamette Research and Extension Center (NWREC) to use as a research test bench for LATERAL in collaboration with NWREC research faculty during this funding period. We have plans to use the aquaponics system as a demonstration project for tour groups to the Research Station, and for future Community Extension farmer workshops and students' research. Indeed, in March LATERAL collaborated with NWREC faculty to host tour groups interested in learning about aquaponics and hydroponics such as students and faculty from the University of Oregon Institute for Health in the Built Environment, Department of Architecture, staff from the Vernier Science Education, and individuals interested in potentially starting up private commercial aquaponics farms. We used a portion of our TABA funds to attend Indoor Ag Con where we conducted over 100customer discovery interviews with farmers, CEA consultants, AgTech manufacturers and suppliers, ag extension agents and CEA faculty from institutions of higher education and non-profit workforce development programs. We hired Dr. Maureen Mathu, a professor of agriculture and aquaponics researcher, to help conduct interviews and perform dialogical analysis to find patterns in the interview data. These customer discovery interviews and the connections we forged at the conference have led to more in-depth follow up conversations with conference participants about CEA monitoring requirements and their experiences training workers to build data literacy. The conversations are providing important insights into workers' learning progressions that will be useful for future workforce development program planning and thinking through how the LATERAL monitoring tools can contribute to teaching and learning. How have the results been disseminated to communities of interest?We are currently taking a "rolling thunder" approach to dissemination to specific communities of interest related to the CEA industry and organizations that provide business development support services rather than making premature announcements since we are in the early startup phase of our company. That said, we are actively involved in networking with a select group of professional organizations, institutions of higher education, and government entities on specific initiatives to ensure that our technology meets specific needs in the CEA industry. For example, LATERAL used TABA funds to hire a professor of agriculture and aquaponics researcher, Dr. Maureen Mathu, to help conduct customer discovery interviews at a professional conference and find patterns in the interview data. We then integrated these data with previous customer discovery interviews and our literature review to gain important insights into CEA workers' AgTech data literacy learning progressions. Program Director Wells then provided a talk at the Aquaponics Association conference in Dallas, Texas in September, 2024 to share our approach to supporting data literacy development with our UI design and proposed a learning progression scoring guide to use in farms and CEA workforce development programs. Later that same day, she then participated as a member of a speakers panel to talk about value of automated, consistent monitoring to reduce risks and improve efficiencies in the farm. These presentations stimulated a large number of conversations within the audience groups and following the conference about workforce development to ensure that the monitoring tools LATERAL provides are useful for both short term tactical decision making and for providing evidence to support longer term strategic planning. Examples of our growing network of organizations we maintain consistent communication with include: IOTech Systems, LLC, Technology Organization of Oregon (TAO), CEA industry professional associations: Aquaponics Association, Aquaculture, Association, Indoor Ag Con community, and the AgTech Innovation community, Strategic Economic Development (SEDCOR) of the mid-Willamette valley, Oregon, Ag Launch, a partnership organization with SEDCOR networking AgTech entrepreneurs and farmers, Oregon Entrepreneurs Network, University of Arizona Center for Innovation, Farm Tech Society, Business Oregon, Oregon Small Business Development Center, Clackamas Center, City of Tucson Office of Economic Initiatives, Phytobiomes Alliance, Open Commons, Intel Corporation, The USDA Urban Service Center, Portland region, Urban Systems. Examples of our growing network of educational institutions we maintain communication with and in the cases of the universities, are planning future educational research and programming with include: Oregon State University North Willamette Research and Extension Center faculty, University of Arizona Controlled Environment Agriculture Center research faculty, Cornell University, College of Agriculture and Life Sciences, School of Integrative Plant Sciences faculty, Lethbridge College, Aquaculture Centre of Excellence, Santa Fe Community College, Controlled Environment Agricultural Program, Vernier Science Technologies, Education Department, Oregon Nursery Association, Educational Department. What do you plan to do during the next reporting period to accomplish the goals?Our primary foci is on completing end-to-end integration of our middleware and Go-to-Market planning. What follows is a brief overview of our R&D roadmap for the NIFA Phase II effort in the next reporting period: With the sensor data pipeline architecture complete, we can now inject rules and future data analytics as the basis of our sensor behavior cause and effects detection. Here, our engineers will inject deeper initial analytics into our LATERAL microservice; we will be primarily focused on refining the architecture we have been working on within this funding period. We are continuing to build on the optimal and operational tolerance range table for plants and fish commonly grown in commercial CEA farms and continuing to find additional confirming evidence to support those set points, Continue to integrate our UI frameworks, Extend field testing beyond our lab bench, Draw on insights gained from field testing to refine the design requirements for our sensor arrays, Continuing to work on data security, Continue customer discovery interviews, Work with members of the Farm Tech Society, the Aquaponics Association, and university faculty to refine the word choices for our mediation options message notifications and to explore opportunities to improve our UI design, Use TABA funding to further assess various business model choices to inform our choices, Use our TABA funding to refine our Product Requirements Development document (technical development roadmap) for release candidates one through three, Use our TABA funds to further develop our Go-to-Market plan and refine the draft Market Requirements Document in alignment with the Product Requirements Development document.
Impacts
What was accomplished under these goals?
LATERAL is pleased to report significant progress towards our NIFA Phase II goals within this reporting period. Goal 1: Advance development of our edge platform in preparation to launch the first version of LATERAL monitoring services Objective 1: To advance the definition of the architecture of the LATERAL monitoring platform so it's modular and maintainable. A major engineering effort involved architecting our LATERAL microservice in a modular way. The sensor data stream has been a primary area of focus during this reporting period. Prior to the beginning of this grant, we revised our architecture to enable dynamic device profiles. Then, during the NIFA Phase II grant funding period our engineers developed the beginnings of the LATERAL APIs that leverage our middleware edge services our UI that advanced analytic microservices will utilize. Engineers conducted pilot testing on a live aquaponics lab bench to run first integrations of our sensor suites with the LATERAL Edge Platform. Based on preliminary validation tests, engineers revised our device profiles to include our sensor dataflow pipeline with advanced rules to monitor operational sensor data ranges. Another significant effort was realigning LATERAL's database architecture in the integration of the time series database that describes the assets of a farm growing system and its relevant monitoring components.We have now laid the foundation for data tagging so that farmers can indicate dimensions and locations of specific regions of each plant bed and what is planted in each region. This will enable advanced machine learning capabilities to include monitoring different tolerance range monitoring set points for distinct regions within each plant bed. Goal 2: Complete development of the v1 edge platform Objective 1: To productize microservices on EdgeX. LATERAL's engineers have made progress integrating the initial notification architecture into the microservice. We have advanced the rules engine and UI development. Our engineers have tightly integrated a Grow Profiles tolerance range alerting mechanism into our UI. Importantly, alerts will now be managed in a way to reduce the amount of over reporting. Further exploration on security requirements is currently ongoing. Objective 2: To prepare our conceptual sensor array prototype for field testing. We significantly advanced our UI development. We now have the ability to overlay multiple sensor data for visualization and developed a pilot ready UI; the framework is in place for field testing. In addition to providing default grow profiles provided by LATERAL (i.e., optimal and safe ranges for each monitored parameter), our engineers made progress developing UI features so that farmers may build their own catalog of custom grow profiles. Farmers can also adjust LATERAL's default set points for individual sensor set points, thus customizing LATERAL's profiles as unique "recipes". Farmers will save their own custom recipes to their local system and maintain ownership over the customized set points or entirely unique Grow Profiles they create. LATERAL will extend the capability of sharing their customized recipes adapted to specific cultivars or growing conditions with others if they so choose. Objective 3. To inject preliminary AI capabilities into the stack. LATERAL's engineers have been able to visually detect sensor behavior and are able to intercept the sensor data pipeline for analytics to enable future ML development to deliver AI capabilities. For example, we are able to visualize the effects of changes of CO2 levels on water pH. As the level of atmospheric CO2 increased in a closed aquaponics lab space the water pH gradually decreased over time. When the lab was vented and CO2 was released, the pH level corrected within the hour. Charting biochemical interactions, including cascading effects amongst measured parameters, is a significant step towards designing programming models we can use to detect and predict cause and effect relationships using AI. Goal 3: Conduct a technical field test program to advance critical enabling features of our conceptual platform for commercialization. Objective 1: To add temporal relationships to our machine learning programming models The LATERAL team validated a series of "off the shelf" sensors and sensor arrays with our aquaponics research bench. The first technical testing stage is well underway using this lab test bench to proactively monitor water quality and atmospheric conditions of a live working grow system. Engineers are performing initial validation of our LATERAL platform and middleware with integrated sensor suites and collecting live data in the lab bench as a precursor to prototyping advanced machine learning and early analytic capabilities. Thus, the foundation is in place architect capturing temporal data sets in our field testing program. Objective 2: Collaborate with farm stakeholder groups to test and improve the platform. In 2024 we attended the Indoor AgTech Innovate conference in June, the Farwest Conference in August, Indoor Ag Con (conference) in March, the Aquaponics Association conference in September, and the Cornell Aquaponics Short Course in March for the purpose of learning about farmers' requirements and to strengthen our network amongst CEA experts and emerging CEA farmers. The conferences and course provided LATERAL opportunities to conduct hundreds of customer discovery interviews including sharing the pilot dashboard views with stakeholders to test and receive feedback on ways to fine tune our product to meet farmers' practical needs. Individual customer discovery interviews, user group interviews, and literature we read have been highly impactful on our UI design process. For example, we received confirming evidence from farm owners, managers, and workers that a large number of farm workers in indoor farms possess low levels of data literacy and little-to-no prior agronomic knowledge. In fact, one interviewee told us that an average of 60% of the new hires her employee recruitment agency places in indoor farms quit within the first 90-days due to a lack of agronomic knowledge and fear of asking for help. The UI development team has been intentionally scaffolding the complexity of representations of data to gradually ease workers in to understanding data values and data analytics and adjusting iconography to accommodate for considerations such as various types of color blindness. We received repeat confirmation that cognitive overload when alerts and alarms go off is of high concern amongst farm owners, managers, and novice workers. Farmers confirmed that pairing alerts and alarms with written message notifications of mediation options to remind workers of their choices when one or more monitored parameter is approaching or exceeding a tolerance range set point has a high potential for reducing cognitive demand and stimulating quick-witted action. Several farm managers specifically mentioned that mediations options are likely to empower novice workers to bring specific questions to mentors rather than ignoring signals out of fear of appearing incompetent. We have been fortunate to have received feedback on our draft message notifications language from a number of industry members and have refined the phrasing to make it more accessible to a wider user group who read and speak English of at least a sixth-grade learning level. We also recently began working with members of a professional organization known as the Farm Tech Society to continue refining the phrasing of the written mediation options prompts.
Publications
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