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AI-Driven Crop Planning Platform for Precision Agriculture Firm

Modernizing Poultry Farms with Internet Connected Feed Level Monitoring

Little Bird Systems approached Lofty Labs to create a customer facing application to allow users to monitor data generated by their innovative audio-based sensors for feed bins in the poultry industry. The team had deployed sensors on multiple farms and were storing data in a database, but had no user interface for analytics, reporting, or even internal oversight. The team also anticipated large scaling challenges with their architecture in the short term future as they prepared a large go-to-market strategy for their IoT (Internet of Things) enabled sensors.

Little Bird Systems team during a discovery workshop at Lofty Labs Lofty Labs worked with the team at Little Bird Systems to re-architect the pipeline of their sensor data using a standardized API (Application Programming Interface) over the internet, allowing their devices to passively push data into the cloud. The API became the standard interface for retrieving data as well, and Lofty developed an interactive reporting interface to surface insights to Little Bird System’s customers. The API and analytics application support an ACL model that allows for flexible governance of data access where Little Bird's employees and customers can access only the data they are granted, without compromising the confidential data of other customers. LBS On ScreenLittle Bird's IoT infrastructure is now poised for massive scaling and sensors are being rolled out to multiple commercial farms. The API powered dashboard is in use by LBS employees, farm employees, and integration partners to efficiently monitor and replenish feed levels. Native mobile applications are now in development, taking advantage of the API at the architecture's core to provide consistent experience across devices. These applications can be developed at a substantially reduced cost as they leverage a pre-existing cloud architecture and data access. Little Bird Systems is now confidently approaching some of the largest poultry integrators in the world with the knowledge that their automated systems can scale to meet demands of any size

Our client had already developed a disruptive proprietary machine learning model to optimize resource utilization and maximize yields in commercial agriculture applications. Armed with real, impactful results from their own research farms and paying customers clamoring for insights they set out to develop a commercial product. But these models need lots of data, and the data needs thorough cleaning and formatting. All of this took weeks or months to process by hand and ultimately ended up in a printed report. The reality was, many of the results from the AI are best delivered in an exploratory visual format. Our client needed to enable their customers to upload massive amounts of data, visualize the data before and after processing, and finally scale out their AI model in the cloud in order to be successful. The primary goal was increasing throughput in order to meet customer demands.

Fortunately, the team at Lofty is well versed in the language and tooling of Data Science. We assembled a small, agile product team to tackle 3 major initiatives: A platform for the storage and processing of customer data A web based application to interface with customers for data collection and insight reporting A scalable cloud infrastructure to automate and distribute the data science and machine learning workloads running behind the scenes We brought our expertise in API development, AWS infrastructures, containerization, and data-driven design together to build an incredible platform that is poised to go very, very big.

Kubernetes, Django, Docker,, vue.js, Celery. If you're not in the business of software development that probably looks like word salad to you, but those are just a small selection of the cutting edge tools all working in concert to deliver high-value insights to the user.

The platform is designed for rapid scalability, and capacity to handle additional customer workloads can be added within minutes. The capacity of the infrastructure to handle larger and larger workloads is virtually unlimited.

Full automation of a 1,000 acre farm has been reduced to less than 30 minutes of work for the customer and just a few hours for our client, with plenty of additional optimizations and full end-to-end automation on the horizon. Previously, this had taken as long as 3-6 weeks. That's a 95-97% reduction in processing time, or a 2400% increase in throughput. Woah. Needless to say, we're excited to see how things pan out for this project. Our client is just getting started and we have only scratched the surface of what has been enabled through this platform. It's made a huge difference already.