Dairy Analytics

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Farmers are rational economic agents and citizen data scientists; they have to deal with the economic problems and pressures of running and maintaining a farm, as well as taking care of their families & keeping their legacy. In their own decision-making domain, farmers make the best use of their resources in such a way that, often, experts overlook their effectiveness in doing so. Usually, the farmers’ income comes from external sources by selling their crops-- in this aspect, milk is significant. As a crop, milk is not only lucrative, but also efficient. Typically, agricultural crops take at least three to six months to reach maturity from planting to market. Milk, on the other hand, provides immediate cash to farmers and helps them manage long sales cycles of crops.

In 2021, India was the world leader in producing raw cow's milk (108300000 tonnes), followed by the United States of America (102629025 tonnes), China (36364198 tonnes), Brazil (36364198 tonnes), Germany (32506910 tonnes), Russian Federation (32078587 tonnes), France (24778840 tonnes), Pakistan (22189150 tonnes), New Zealand (21886376 tonnes), and Türkiye (21370116 tonnes). The United States produced most of its milk in California, which alone accounted for almost 19% of the nation's milk production in 2021. Seven (7) states had over 10 billion pounds of milk production in 2021: California, Wisconsin, Idaho, New York, Texas, Michigan & Pennsylvania.

Also, for whole fresh buffalo milk in 2021 worldwide, India was the top producer of whole fresh buffalo milk (94383691 tonnes) among countries, followed by Pakistan (36444850 tonnes), China (2905806 tonnes), Egypt (1567503 tonnes), Nepal (1419412 tonnes), Italy (257460 tonnes), Myanmar (176137 tonnes), Iran (Islamic Republic of) (128000 tonnes), Indonesia (91425 tonnes), and Sri Lanka (87935 tonnes). The data presented is from the Food And Agriculture Organization (FAO) of the United Nations.

Production - Milk, Raw milk of cattle - 2021
Source:Food And Agriculture Organization of the United Nations

Production - Milk, whole fresh buffalo- 2021
Source:Food And Agriculture Organization of the United Nations

We provide a Data Science and Analytics platform that helps with Dairy Analytics, Agriculture Analytics, Crop Yield, Profit optimization, and tailored advice for small farmers. Our platform focuses on Food Security and links Crops, Macroeconomics, supply chain, and pricing using economic models. Our platform also uses linear heuristics to improve the yield at the farm level by integrating heuristics from the farm level and small farm producer level.

Our Customers

Our World class analytics is for our World class farmers and agricultural equipment manufacturing companies:

Small Farmers & Producers
Advanced Analytics to help farmers to optimize Crop patterns and reduce farm input costs .

Banks & Insurance Companies
Proactive Analytics to help Banks and Insurance managers to better plan mitigating market/climate/crop risks.

Agricultural Equipment Manufacturers (Fertilizers, Tractors, and others)
Farm Heuristics help Fertilizer and Farm Equipment companies to optimize supply chain and reduce costs.

Food Industries
Agricultural Co-operatives, Retail Food Chains, and Food Industries .

State & Local governments
Macroeconomic, Agricultural, and Food Security Advanced Analytics help Governmental and Local/State Institutions to better plan Food and Nutrition Security.

Research Laboratories
Real-time Farm & Sensor Data will enable research institutions, Farm manufacturers, and Fertilizer companies to better plan product based on the geo-location & climate variants.

Hanumayamma is a leader in developing a Machine Learning based analytics platform that uses data from our Dairy Cow Necklace sensors and enhanced data from Geolocations, as well as global data sources such as FAO. Data Analytics are helping us create new, innovative data driven products that allow farmers & agricultural companies to interact with their customers in a unique, and disruptive way. For example, Connected Dairy Analytic-- a dairy analytics and big data platform-- delivers large operational efficiencies, cost savings, and actionable insights to solve dairy cattle related, critical issues. Connected dairy, importantly, is a data enabled insightful tool that helps the better management of dairy activities.

Try our Milk Price Predict Model

You can access our current Milk & Agricultural Commodities Machine Learning Model through the button below; Our AI model is built on top of USDA and FAO Datasets. The model features the following commodities:
  • Corn - Corn stalks are a cost effective means of ration for lactating cows, or those ready to produce milk; acknowledging this, it is important for producers to exercise caution when using corn stalks as ration and not add them at excessive inclusion rates.
  • Wheat – The process of grinding wheat into flour produces both human and animal food. Wheat becomes a desirable feed component for the cattle, swine, and poultry industries when the price difference between corn and wheat decreases. Both Hard Winter Wheat, which typically has high protein content, and Soft Winter Wheat--usually lower in protein-- work well as feed for dairy animals.
  • Soybeans - Incorporating soybeans and their byproducts in the rations for dairy cattle is a fairly common practice. Soybeans are an excellent source of essential amino acids and they fit into any type of forage-based ration. Soybeans, when properly heat treated, can provide additional rumen undegradable protein (RUP) and fat; soybeans that have not been heated serve as a source of degradable and soluble protein.
  • Sorghum – Sorghum contains more crude protein than corn. Thus, sorghum grain is both interchangeable with corn in the diets of lactating dairy cattle, or can serve as a replacement for corn altogether. Although research has shown sorghum grain to be comparable to corn in lactating dairy cow diets, the market often values sorghum less than corn.
Basic Commodities to Milk Price
Source: The USDA and FAO


Cow Necklace
The Cow Necklace is Hanumayamma's CLASS 10 USPTO approved diagnostic sensor. The sensor collects details regarding the vital signs and activity of a dairy cattle to help farmers better manage the health of the cattle.

Precision Dairy
Small farm agriculture is an economic multiplier at the gross root level and has a huge positive influence on the Gross Domestic Product (GDP) of both a singular country, as well as the collective global Gross Domestic Product.

A Dairy Analytics Platform provides a complete view of sensors installed in dairy farms; at an aggregate level, it is a vital planning tool for dairy cooperatives, local governments, and the agriculture industry.

Cost Optimization
Dairy farming is an expensive business that consists of both internal and external expenses: Feed, Clinical, Chemicals/Medicine, Human Labor, Equipment, Finance, Operations, Security, and Transportation.

Connected Infrastructure
Agriculture is filled with uncertainties, risks, losses, and back-breaking work-- yet, the returns on agriculture-- especially for small farmers-- are miniscule or, in some cases, non-existent.

data partners

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Cow Necklace

A Wearable Veterinary Sensor
We are happy to announce that we have obtained our product classification trademark (TM) from the United States Patent and Trademark Office (USPTO). This means that we are now CLASS10 device manufacturers. The CLASS 10 classification is usually given to medical devices such as surgical, medical, dental and veterinary devices and instruments; artificial limbs, eyes, and teeth; orthopedic items; suture materials. In particular, we have been granted "Class 10: Wearable veterinary sensor for use in capturing a cow’s vital signs, providing data to the farmer to monitor the cow’s milk productivity, and improving its overall health".

Cow Necklace

Waterproof Sensor Enclosure
We found out from our field analysis that Dairy IoT sensors work better and last longer with a waterproof sensor enclosure; this way, dairy management can keep doing their usual day to day activities or process without any changes.

Edge Module
The Sensor Edge Module allows real-time and useful insights for dairy management to be delivered. We have developed the Sensor Edge Module to work with low and intermittent network connections, so that our analytics can offer the most precise and relevant insights for the dairy industry.

Environmental, Social, and Governance (ESG)

Sustainability Platform
Hanumayamma Innovations and Technologies, Inc. offers a Sustainability Platform for reporting and analytics, with a focus on agriculture and dairy industries.
Hanumayamma Environmental, Social, and Governance (ESG) Platform - Designed to help dairy and agricultural farms, cooperatives, and food processing units of different sizes achieve their environmental sustainability goals and improve the world.

  • Data Collected at Small, Medium, and Large Dairy Farms across the World.
  • Worked with Small, Medium, and Large-Scale Agricultural Farms, Cooperatives, and Food Processing Units
Hanumayamma Sustainability Platform

Data and Analytics
Data and analytics are at the core of Hanumayamma’ s approach to accelerating sustainability progress.
Hanumayamma Sustainability Platform uses Hanumayamma Dairy & Agriculture Cloud to gather data from various dairy and agricultural sensors, such as Cow Necklace, Class 10, veterinarian diagnostic sensor, and creates a common data model. It then converts different data to provide insights on Water, Methane, Milk, and Green Analytics and helps farmers to act on them.

Hardware that captures Methane emissions from Small, Medium, and Large Dairy Farms and upload to Hanumayamma Cloud.
  • Patented edge analytics that monitor the onset of increased Methane emissions.
  • Identification of Yield changes
  • Water Usage
  • Feed Intake

Data + Agriculture, Dairy, Specialty Crop Analytics & AI at the core accelerates sustainability progress

Sustainability Manager
Hanumayamma’ s Sustainability Manager empowers organizations to turn data insights into action and reduce environmental impact.

Hanumayamma’ s platform allows organizations to calculate their sustainability footprint, analyze ESG performance against goals, and provide data governance.
This is how platform process data: first, it uses Hanumayamma Cloud for Sustainability data model, which enhances field sensor data, weather & satellite, and econometric data. Second, the data is analyzed with Hanumayamma’ s data science algorithms to produce ESG calculations and tracking for each tenant. Lastly, it produces customized data insights for compliance and governance reporting purposes. Actionable steps and progress towards objectives are the outcomes that help us & world achieve ESG goals.

Precision Dairy

Milk Fever
Milk fever is a condition that commonly occurs in dairy cows near the time of giving birth. It is a metabolic disorder that results from a lack of calcium in the blood (hypocalcaemia). It affects between 3 to 10% of cows in dairy areas each year, and some farms have much higher rates.

  • Patented algorithms based on accelerometer & cattle movement activity
  • Identification of halts, or stillness, in activity
Cow Necklace Activity Capture

Ketosis is a condition in cattle where energy needs-- for instance, the higher output of milk-- are higher than energy consumption, leading to a reduced, or “negative” energy balance.

Our Sensors identify onset of Ketosis Symptoms:
  • Patented edge analytics that monitor the onset of increased activity.
  • Identification of Yield changes
  • Production
  • Feeding

Cow Necklace Activity Capture

Rumination is the natural process of bringing fibrous food from the rumen to the mouth and back to the rumen in cattle and other animals called ruminants. Rumination is not only essential for healthy cows; it can also signal stress or sickness early on. Rumination is influenced by both diet-related factors-- such as how much fiber is in a feed, the form of fiber, and how well it is digested - and how the rumen works internally, but a cow will adjust rumination according to external stressors on any given diet. Stress can be measured by how much rumination time changes from the herd’s or the individual cow’s normal rumination time, 48 hours before other signs show up. By tracking drops in rumination times, management changes can be done to reduce stressful situations, or to start treating a sick cow. Our sensors allow farmers to set and capture rumination threshold counts, which help them spot possible changes in rumination patterns, and treat cattle accordingly.

Lameness makes cattle suffer, which weakens them and lowers productivity. The financial impact of lameness involves losses from reduced production, treatment expenses, longer calving interval, and possibly extra labor. Less milk of 1.7 - 3 L/day for up to 1 month before and 1 month after treatment due to pain, and milk wasted because of antibiotic therapy must also be taken into account. Our sensors detect lameness signs, and help farmers to deal with them appropriately. Our Sensors detect Lameness (proactive) Signs:

  • Built-in Machine Learning Algorithms that Detect Lameness Symptoms
  • Cloud Enabled In-Memory Grids that Compare Behavior vs. Health
In Memory Grid: Real time Machine Learning

Healthy vs. Sick Cattle Detection
Our Sensors identify healthy-vs.-sick cattle:

  • Patented Algorithms based on accelerometer & cattle moment activity
  • Behavior Change

Commodity Markets

Predicting the prices of commodities is crucial for making choices about how much land to plant or harvest crops on and the economic health of small farmers. The anticipated prices of agricultural commodities can affect the farming and ranching decisions of how much land to use for crops or how many animals to keep and, as a result, impact the availability of agricultural commodities.

A farm’s financial health is also influenced by changes in commodity prices. For example, when commodity prices are low for a long time, farm incomes go down and farmers depend more on credit, making them more exposed to higher interest rates and other economic shifts. When commodity prices are high for a long time, farm incomes go up and farmers become more resilient to economic changes. Changes to commodity prices also affect food security: when prices are low for a long time, consumers can buy enough food more easily, while when prices are high for a long time, their food security is reduced, especially in developing countries.

Agricultural product prices have some unique characteristics and need special attention. Agricultural Commodity Markets are affected by macroeconomic environment, oil prices, supply/demand, consumer tastes/preferences, bad weather conditions, biofuels, stock to use ratios, dollar exchange rates, speculation, food storage, speculative activity, financial markets, fertilizers, trade restrictions, wealth of nations, and other economic factors.

Commodity Markets
Source: The World Bank


The Hanumayamma Analytics platform examines the credit given to agriculture by the private/commercial banking sector in over 120 countries, which includes loans to producers in agriculture, forestry and fisheries, such as household producers, cooperatives, and agro-businesses. The Hanumayamma Agriculture Analytic platform uses statistical techniques and econometric models to generate customized recommendations for local farmers, with the aim of providing advanced insights to cope with any changes in macroeconomic conditions, while ensuring the profitability of small farmers. The Hanumayamma agriculture platform relies on credit to agriculture data for its Commodity Models and Risk Models, which constantly evaluate global market conditions to protect the small farmer.

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Dairy Analytics Platform

Analytics platform consists of two core engines: Machine Learning and Recommendation Engine

The goal of our ML and rule processing is simple: provide actionable insights to dairy farmers. Technologically, ML and rule processing are performed at both a dairy sensor level (closer to cattle in dairy farms) and in the Hanumayamma Dairy Cloud.

Pattern Detection: We have created various supervised and unsupervised machine learning algorithms as part of the Dairy Analytics platform. We have examined several dairy streams in real-time and built decision trees that follow the industry standards and can use the best proprietary machine learning algorithms ( USPTO - Patent Pending ). We can use Machine Learning and Pattern detection to find out how different dairy optimization factors are related, such as how medication, vitamin intake, output, and seasonal factors affect the health and milk production of dairy cows.

Historical Analysis: Historical analysis considers how seasonal factors like heat stress (HS) and pneumonia affect the milk production of dairy cattle. Also, our architecture connects the weather forecast-- that is, the expected weather conditions in the next weeks-- to the historical observed responses of dairy cattle. For example, if dairy cattle exhibit signs of sickness due to rapid temperature changes, our architecture offers practical advice to dairy staff by checking for any sudden or future weather changes and promptly notifying them of any such events.

Recommendation System

We provide a dairy recommendation system that helps manage food optimization, medication suggestions, optimal dairy settings per cattle, and disease management. We have created a dairy recommendation engine that combines various data sources that account for both dairy context and location details (USPTO - Patent Pending)

We use both content and collaborative recommendation systems. The main goal of the collaborative recommendation method is to create network benefits in terms of cattle disease analysis, medication, and milk productivity.

Smary Notifications: One of the key aspects of our recommendation system is to rank the notifications that dairy management and operation staff get and show them in a way that prevents alert overload. We have studied different dairy farms - big and small - where systems such as milk production, weather, temperature, health, and location generate many notifications per day; this can disrupt dairy operations, and therefore lower overall productivity, if not managed well.

Social presence Analytics: Our recommendation system uses location based social presence analytics to deliver the most useful information for dairy management. By using social presence analytics for dairy management, cattle health management becomes much better, and, at the same time, dairy farms can work together with the local community.


Cost Optimization

Farming is a costly process that involves both internal and external costs; some of these costs are feed, fertilizers, human labor, equipment, finance, operations, security, and transportation. Fertilizer is a major cost for most grain farms, but its percentage as a crop cost varies among continents and countries. For instance, fertilizer is the main source of serious debt for small farms in India. Also, the price of agricultural fertilizers has a huge impact on the total yield and production of maize in Malawi.

To forecast the price of fertilizer would benefit developing economies in many ways, and also have a life-saving impact on them. For example, fertilizer price prediction would lower the debt of farmers. A 2018 study by the National Bank for Agriculture and Rural Development in India found that 52.5 percent of all agricultural households had debt, according to current banking rules that prevent farmers with existing loans from getting more credit. Therefore, indebted families who need credit often force female farmers to take loans, which worsens the debt cycle that is very common in the western Indian region and in many developing countries where farms have fallen into cyclic debt due to the cost of fertilizers and low crop yields. According to data that came out earlier this year, India had 93 million microfinance accounts, mostly belonging to women in self-help groups; an increase of 22 percent from the year before. Microfinance lending rates are much lower than those offered by private money lenders, who flourish in these areas.

Commodity Markets
Source: The World Bank


The Hanumayamma Analytics platform offers the best cost reduction for lowering fertilizer expenses for small farmers. Hanumayamma's analytic predictions and heuristic linear programming modules give practical guidance to small farmers on how to use fertilizer efficiently and cut down agricultural costs- seeds, equipment, fertilizer, human labor- leading to a more prosperous and abundant world with wealthy small farmers.

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Risk Modeling

Agriculture is a sector that involves many uncertainties, risks, losses, and hard work. However, the benefits of agriculture-- especially for small farmers-- are very low or, sometimes, non-existent. It is understandable that many small farms, in the U.S.A and other countries, have vanished. There are two types of risks that farmers face: internal and external farm risks. Internal farm risks-- risks related to soil, fertilizers, crop growth stages, and personal/family issues-- are manageable by farmers. External risks, on the other hand, are outside a farmer’s control; examples of such external farm risks are commodity price fluctuations, macroeconomic conditions, unexpected effects of real-time price models, trade conflicts, sudden shifts in people's preferences & opinion of a food commodity, and global climate change.

Risks from how climate change & weather events affect agriculture are important for every industry and service sector of the economy. One could say that weather events leave their mark on macroeconomic indicators and Gross Domestic Product (GDP). For example, the direct impact of weather events can be seen in construction, retail, agriculture, oil & gas, entertainment, travel, and public health. The weather influences the project cost estimation, schedule, delivery, and productivity of business-related activities of these industries. Adaptive analytics is crucial for understanding and planning for how weather events affect agriculture.

The combination of commodity models and weather model events with the addition of ensemble machine learning models are the best signal gatherers; they can forecast crop production and give information about the history of weather events to reduce small farmer risk.

Top 10 countries - Credit to Agriculture
Source: Food and Agriculture Organization of the United Nations


The Hanumayamma Analytics platform processes climate data, storm data, and weather data constantly to refresh agriculture risk models that can help small scale farmers understand the impacts of climate change on agriculture outputs. Our aim is clear and simple: every farmer should have access to artificial intelligence enhanced insights, and the knowledge they can offer. This is a tool that everyone across the globe should have!

More on Democratization of Artificial Intelligence for creating a sustainable food future, please check our published thought leadership paper: png
More on the role of combinatorial mathematical optimization and Heuristics, please check our published thought leadership paper: png