Livestock monitoring

RoadAthena is an AI-powered road condition monitoring and reporting solution in India that helps digitize and assess road infrastructure at scale.The platform processes large road video datasets to detect conditions, anomalies, and road assets, supporting more effective infrastructure management across a vast road network.Google Cloud provides scalable compute and storage for the workload, while Google Maps API is used for mapping, boundary, and jurisdiction context.

RoadAthenaPublic Sector

Kami Vision, an intelligent camera solution provider, launched generative AI-powered home security solutions within one month using Amazon Nova Lite on Amazon Bedrock.The company says the new solutions preserve 94% video recognition accuracy while reducing inference costs and token consumption per inference, and they support video question answering and event notifications for home security and elder care.Kami Vision also cited global compliance requirements and the need to balance cost, speed, and accuracy in video analysis as key drivers for adopting AWS.

Kami VisionOther

Coles, a leading Australian supermarket chain, implemented an innovative digital platform to unify AI workload management and enhance the retail customer experience. Using Microsoft Azure Stack HCI and Azure AI with NVIDIA GPUs, Coles introduced Computer Vision for high-accuracy produce recognition at checkout and queue monitoring at deli counters. The company developed the Intelligent Edge Backbone (IEB) platform to centralize data, orchestrate AI workloads, and deliver real-time event notifications to staff across its extensive network of over 1,800 stores. This system streamlines checkout, reduces customer wait times, and improves operational efficiency in a way that is privacy-conscious—ensuring the technology does not identify individuals or collect personal data. The initiative is described as a global-first for retail, enabling immediate actions like staff alerts or system notifications to improve service readiness and customer satisfaction.

ColesRetail

CRV, a Dutch cattle improvement cooperative, leverages Microsoft Azure Red Hat OpenShift to transform livestock farming into a more data-driven and sustainable practice. Operating in countries like Belgium, New Zealand, South Africa, Brazil, and the US, the organization provides farmers with AI-powered insights to enhance cow health, efficiency, and sustainability. Leveraging data from genomics and environmental factors, CRV helps farmers achieve longer-living livestock, better herd health management, and minimized carbon footprints. By addressing the agricultural sector's need for sustainability, CRV exemplifies the impactful synergy between technology and farming.

CRVAgriculture

Techion, a New Zealand-based agriculture technology firm, partnered with AI specialist Aware Group to address the pervasive challenge of parasite infections that affect livestock health and farm productivity. Traditionally, manual parasite detection was labor-intensive, slow, and expensive, leading to widespread preventative drenching of animals. This practice contributed to rising costs, inefficiency, and drench resistance, costing New Zealand farmers tens of millions of dollars annually.Techion developed the FECPAKG2 platform, which integrates portable digital microscopes (Micro-I) with cloud solutions and AI. The new system leverages Azure Machine Learning to analyze images of faecal egg count samples and provide rapid, automated, scalable diagnostics for parasites across various livestock.The platform's AI features, running on Microsoft Azure, allow farmers and veterinarians to receive accurate FEC results within seconds, enabling targeted and timely animal treatment instead of blanket medication. This not only boosts productivity and animal welfare but also mitigates the risk of overmedication and environmental harm.By scaling their diagnostic services globally and automating much of the manual analysis, Techion dramatically reduced the need for skilled human technicians and improved service delivery speed. The solution is now deployed for cattle, equine, pigs, and birds across regions including Australia, the UK, and more.Their approach exemplifies how cloud AI and local partnerships can create transferable digital diagnostics, with applications reaching beyond agriculture to broader animal, environmental, and human health issues. Future plans include building a global database of diagnostic images and forging additional partnerships to tackle complex health problems.

TechionAgriculture

Multiple farms in the agriculture industry faced difficulties counting and tracking livestock in remote areas without constant cloud connectivity, leading to inconsistent and inefficient manual counting.They used Amazon SageMaker's built-in object detection model, optimized with Amazon SageMaker Neo for edge devices such as NVIDIA Jetson Xavier, to detect livestock in video streams.Deployment and management of edge models and applications were handled via AWS IoT Greengrass V2, which allowed running inference and counting livestock near real-time at the edge from live camera streams.This solution improved operational efficiency with consistent and accurate livestock counts, reduced manual counting errors, and enabled workers to focus on higher-value tasks.

Multiple farmsAgriculture

The CSIRO and Aak Puul Ngantam (APN) Cape York Indigenous rangers partnered with Microsoft to develop an AI-powered system to streamline threatened turtle nest and predator monitoring on Australia’s remote northern beaches. Previously, manual surveys took a month to complete, hampering conservation efforts. Using Azure cloud, AI for Earth, and Power BI, drone and helicopter photos are efficiently analyzed with custom-trained models to identify turtle nests and predator tracks. Results are delivered via Power BI dashboards, enabling rangers to act rapidly and adapt predator control efforts in real time. The collaboration integrates Indigenous knowledge and state-of-the-art technology and has demonstrably reduced nest predation rates and improved hatchling survivability. The pipeline approach is replicable for other environmental management applications.

CSIROAgriculture

Norway Royal Salmon (NRS), a leading Nordic aquaculture company, produces around 70,000 tons of salmon annually. Operating in harsh northern Norway, NRS sought to improve operational efficiency, worker safety, and environmental sustainability in salmon farming.Partnering with Microsoft and ABB, NRS piloted an AI-driven analytics solution leveraging Azure Cloud and ABB Ability.The implementation uses underwater cameras to capture fish images in offshore pens, with computer vision and AI to estimate biomass and fish populations.This system reduces reliance on manual, open-sea labor, improves fish health monitoring, and supports data-driven decision making.As a result, the farm can reduce operational costs and minimize CO2 impact, aligning with sustainability goals and ensuring cleaner seas.ABB’s expertise combined with Azure’s scalable cloud supports reliable, real-time monitoring and analytics.This effort exemplifies cross-disciplinary co-creation involving NRS, ABB, and Microsoft, and led to quick solution deployment from ideation to onsite installation.

Norway Royal SalmonAgriculture

The NFL partnered with AWS to develop the "Digital Athlete" platform, using AI, machine learning, and computer vision to analyze player health and safety data and predict injury risk.AWS technologies such as Amazon SageMaker, Amazon Rekognition, and AWS AI/ML services were applied to model game scenarios and concussion-causing forces.The collaboration involves leveraging historical and real-time player data, video feeds, and environmental factors to improve injury treatment, prevention, and rehabilitation.Advanced computer vision models were developed to detect concussions, and the partnership expanded the NFL's use of AWS for real-time NFL Next Gen Stats data analysis.

National Football LeagueOther

CSIRO, Australia's national science agency, collaborated with Microsoft to address the challenge of feral cattle threatening the ecology and economy of Northern Australia. The solution leveraged Microsoft Azure and AI, combined with low-orbit satellite data and indigenous knowledge. This created an advanced system for tracking and managing herds remotely over vast, inaccessible rangelands. The implementation is considered the largest remote livestock management system globally, improving ecological protection and economic safeguards. AI-powered insights help land managers monitor, predict, and reduce the negative impacts of feral animals. The approach integrates advanced cloud, AI, and geospatial technologies for real-time situational awareness, enabling more targeted and humane interventions, while supporting indigenous communities and ecological stewardship. The initiative demonstrates how technology and traditional knowledge can work together to solve complex environmental challenges at scale. The outcomes include more efficient herd management, cost savings, and better ecological outcomes for affected regions.

CSIROAgriculture