Ask Peter's AI chatbot about the Vineyard Plant WhispererThe submit box below, is a general AI Model trained on all information available on the internet as of December 2021. Take the response with a grain of salt because AI chatbots make stuff up. The industry calls it hallucinations. With fine tuning and Retrieval Augmented Generation(RAG), the answers are much better. We have an enhanced AI chatbot that knows more about the vineyard solutions we are implementing. Our RAG uses vineyard research papers and website articles CCA plans to incorporate into it's "Plant Whisper" AI driven robotic platform. If you'd like to try it please contact us. As it require an login account. Example questions for Meta's Llama 3 70 billion parameter LLM general internet trained chatbot:
Ask your question and say "enter that". You have to wear ear buds or mute speech output. Otherwise the chatbot will hear itself and enter what it saying into the prompt text box. Mute speech output |
![]() Peter James Developer of the Wine Grape Whisperer “Any sufficiently advanced technology is indistinguishable from magic.” Athur C. Clarke The fundamental approach the Plant Whisperer is using to converge on working autonomous robotic tasks and on optimal grape growing practices is called genetic algorithms. It follows the same principals as biological evolution. It competes many siblings against each other, picks the best performers and crossbreeds them for the next generation of competitors. Over many generations, the algorithm converges to near optimal solutions.
We believe biological and other natural systems, like weather, can't be
well understood using a deterministic physics paradigm. Rather these systems
are, as Ilya Prigogine termed them, disapative structures. The complexity of
growing high quality wine grapes is better understood when modeled as dissapative
structures using Chaos Therory. Following the "It Takes One to Know One" doctrine, AI
and particularly large language models are a mix of chaos and order and have
the capacity to uncover hidden order from the complexity that is grape growing.
We intend to build an AI and train it in all the data the AI can gather about
grapes and wine making to provide a deeper understanding of the process of
growing them and making wine. I was getting tried of checking to see if a germination tray was drying out. I noticed a reflection off the
surface of the water. The reflection was getting smaller as the tray dried out. So I asked the Plant Whisperer,
if it could watch it for me and let me know when it was time to add water. This 3D scanner provides precise plant component positions to guide robots for precision leaf surface electrostatic spraying, harvesting, cordon training, etc. Our machine vision is trained to detect and outline weeds for non-pesticide removal. It will also be trained to detect, classify and outline all disease conditions, pests and nutrient defincies. This is a low power laser prototype for performing many weed removal, pruning (cane & spur) and cutting tasks (fruit harvest & defoliation) in the field and in the processing center. A higher power laser will be deployed in production. Because the high powered laser cat cut instantly, the dwell time is so low there is no danger of starting a fire. We will be deploying a high speed targeted IR laser to identify and kill up to 20 insect pests per second. This is an $80 sensor that tracks hand skeleton and forearm motion. It can be used to provide remote low cost labor from foreign countries or provide jobs to
disabled persons to perform fields and processing center work. This is our robotic reel mower. It is a small fraction of the cost, weight and energy use of our previous electric ride-on rotary mower platform. It is so safe, you can stick your hands in the spinning blades and not get cut. It gives a better cut. Because reel mowers need to mow more frequently, we can use it as a platform to carry a wide array of sensors and robotic devices to perform virtually all labor tasks in the vineyard. ![]() The mower platform will also serve as an aircraft carrier for a squadron of low cost 3D printed autonomous drones that will fly in close the each vine to inspect trunks, leaves and fruits. ![]() We will also release an army of low cost autonomous RC cars to inspect vine trunks for lesions and pests. it will also be able to leaves and fruits clusters from below adding 3D reconstruction of the vine when the mower and drone views are obscured. This a $30 RC car we have modified to make autonomous. Due to their low cost, we can deploy a small army of these as sensor platforms at a very low cost. Using open source software, three cameras on the robot mower and SLAM maps created by the precision GPS controlled robots, these RC cars and and drones will be able to navigate very precisely around the vineyard. ![]() We'll be modifying this low cost electro-static sprayer for precision applications of pesticides. By directing the robot to hold the nozzle close to the leaf surface the electrically charged droplets will only adhere to the leaf. This will great reduce the amount of pesticides used and keep it off the fruit. We believe between UVC light treatments and precision spraying, vineyards can re-purpose their wide area spray fans to provide air flow to further mitigate humidity related fungal issues. Golf course place fans in dead air spots to prevent fungal outbreaks. . ![]() Soil Tester/sample pneumatic plunger. For soil sample collection and inserting test probes. ![]() Wireless air temperature and humidity sensor. can use WiFi or bluetooth. Will be carried by robots and installed around the vineyard in stationary positions. ![]() Poor man's EC and soil moisture probe. Commercial TDR EC/moisture probes run $100 and up. Using these probes and a low cost circuit will allow us to mount them on many more robots, to provide high precision soil mapping much more frequently. EC reflects the PH and salinity of the soil. Which in turn effects things like nutrient up take by the vines. ![]() pH, EC and temperature test controller. We have a surface mount pick & place machine in-house to produce these in a much smaller footprint and cheaper. ![]() On securing sufficient SCRI funding will produce a 3D micro-fluidics handling device for processing soil, pest and plant tissue samples to perform liquid chromatography and use lab-on-chip technology for DNA analysis in the field. ![]() For tasks like spraying and harvest requiring higher weigh capacities, we will use medium and high powered hub motor wheels to pull trailers, tankers. These will travel along the end of the rows and smaller robots will travel up and down the rows performing tasks. In the cases where precision spraying and UVC light treatment is not adequate to control or prevent disease, the larger autonomous vehicle will tow the large sprayers. This will at least prevent worker exposure to those chemicals. ![]() We will be building many forms of vision agents to feed the Plant Whisperer AI data. Edge detection of vine trunks can tell the AI many things. Such as triangulating the position of the robots, thickness of the trunk (ie. potential yield), help in registering other vision data like 3D, multispectral. We produced this image from a picture image at a local tree farm. ![]() We will be scanning the vines, leaves and fruits in many spectrum both visible and non-visible. Using, normalized difference vegetation index (NDVI), red and near infra-red can tell what is foliage and things like heat and water stress. Green can disclose nitrogen content. ![]() ![]()
In order to optimize grape production, training the grapevine to achieve maximum absorption of photons, uptake of water and nutrients and air flow to prevent fungal disease. This needs to be in a manner the allow access to the vine and fruit to perform other task like mowing, weeding, spraying, trimming, defoliation and harvesting.
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