Public Funding for Icerobotics Ltd

This project involves development of a novel, precision, data-driven solution for dairy farmers that will create a complete step-change towards improved resource use efficiency and net zero emissions. For the first time dairy farmers will be able to calculate and evaluate their efficiency, productivity and environmental impact and then use sophisticated simulation tools, calibrated for their own farm, to identify optimal management decisions in real time. Current on-farm precision technologies often deliver isolated solutions to individual components of complex dairy production systems. This research project will focus on combining data and precision technologies (including cow wearables, novel cow health recording technology, detailed data from milk recording and animal health organisations, genomic data, nutritional data and data carbon footprint and emissions), to create software for a real-time decision support system (Real-time dairy, REMEDY) that will, for the first time, place the application of precision, data-driven, solutions at the finger-tips of dairy farmers. REMEDY will accelerate integration of a diverse range of key data sources and utilise state-of-the-art predictive and simulation models to determine the consequences of specific management decisions on future productivity, animal health, profitability, and environmental impact. Farmer decision-making on a real time basis, will ensure genuine, substantial and measurable improvements in productivity, efficiency, environmental footprint and animal welfare. REMEDY represents a significant step change in the utilisation of farm data and will greatly accelerate the on-farm adoption of new integrated solutions by directly supporting day-to-day decision making. REMEDY will provide deep insights into the consequences of future actions, allowing truly evidence-based decision making by farmers, vets and advisors. The predictive engine of REMEDY will employ sophisticated AI and machine learning methods to continuously use a farm's data to provide farm specific predictions to drive increased efficiency productivity and sustainability. We will ensure REMEDY has relevance and a focus on end-users. To ensure this, we have a team of academics, dairy industry specialists, precision technology specialists, veterinarians and farmers. This team has the infrastructure and substantial proven experience to deliver KE, identify target markets, establish the widespread adoption and support ongoing user needs. We will co-design project outputs with a group of vets and farmers and work with social scientists to evaluate the project outputs and determine best routes to break down barriers to achieve widespread dissemination.

This project supports Biotangents (Penicuik), IceRobotics (Edinburgh) and Cranfield Univeristy in developing an advanced pen-side diagnostic test for brucellosis, a highly contagious bacterial infection that primarily affects livestock and poses an additional and significant threat to humans as a zoonotic disease. While Great Britain is officially brucellosis free, prevalence of the disease has been increasing in China in both animals and humans in recent years. Efficacy of antibiotics to treat brucellosis is variable. Biotangents will develop an accurate pen- side test to facilitate the identification of infected animals and allow the spread of the disease in livestock populations to be better controlled and the risk of transmission to humans, and subsequent demand for antibiotics for treatment, to be reduced. This will be tested in China alongside IceRobotics' behavioural monitoring platform that is able to monitor individual animal health status and shortlist those that may have acquired the disease.

"Ruminants worldwide are affected by Johne's Disease (JD), or paratuberculosis, a fatal and highly infectious disease. JD severely impacts cattle welfare due to inflammation of their intestines, resulting in a profuse diarrhoea and emaciation. JD causes large economic losses due to decreased milk production estimated at over 4000 kg less milk produced in a lifetime, increased wastage of adult animals, increased susceptibility to other diseases: five times as likely to become lame and twice as likely to get mastitis, increased infertility and cost of diagnosis, monitoring and control programmes. Calves are usually infected via ingestion of the causal bacterium, referred to as MAP, present in colostrum or faeces of infected animals. JD is very hard to diagnose due to the long incubation period during which time clinical signs are absent. Furthermore, MAP is not completely killed by pasteurisation and can be present in retail milk and with some evidence it may be associated with Crohn's disease in humans. IceRobotics (ICE), an Agri-Tech producing SME company will lead the project, with Harper Adams University (HAU) as its scientific partner, together with the Dairy Research Centre of Scotland's Rural College (SRUC) and Moredun Research Institute (MRI) as sub-contractors. A study undertaken by HAU using ICE sensor technology already demonstrated that daily lying time is significantly reduced in JD positive cows compared to JD negative cows around peak lactation. ICE will lead the analysis to detect JD from changes in animal behaviour, supported by MRI's world-leading Johne's expertise. Historic high-quality data will be utilised from HAU and SRUC research herds, alongside further new data from the HAU herd. The behaviour of uninfected and infected animals will be characterised and compared using measurements obtained from existing precision livestock technologies providing second-by-second monitoring individual animal behaviour. The novel output from this project will be a new Johne's Detection module to the CowAlert system, enabling ICE to improve its business performance in the UK and internationally. Additionally it will satisfy a market need for more timely detection of a severe and costly disease, at an economic cost. As a result of this project, farmers will benefit from early detection of JD, consequently improved control of JD, higher production efficiency and profitability. Cows will benefit from improved animal health and welfare. Milk retailers and consumers will benefit from less MAP in milk, consequently better food safety and quality. The environment will benefit from less greenhouse gas emission."

The project will develop an experimental system which will demonstrate the feasibility and effectiveness of atomic magnetometer technology for monitoring the health and welfare of livestock. This is a new approach, made possible by recent advances in the sensitivity of atomic magnetometers. The feasibility of this application will involve tests in a real farm environment.

This project is a collaboration between Harper Adams University and three progressive British enterprises: sensor manufacturer IceRobotics, dairy consultancy Kingshay, and dairy company Dairy Crest. It will develop a comprehensive sensor-based engineering solution that enables dairy farmers to improve the health and welfare of their cows through timely and reliable alerting of health issues concerning individual animals, enabling them to take swift action to address animal health problems before they become more serious. The system will be designed to integrate as far as possible with existing farm systems and equipment, and will be fully accessible via mobile devices and over the internet. As well as system development, the project will involve field testing on research farms, economic validation on commercial herds, and various communication forums and events for the dairy farming community.

The Cloud-enabled Robust Intelligent Sensing Platform (CRISP) will enable rapid development and deployment of condition monitoring and alerting systems using wireless sensors in harsh envionments. The new platform will make full use of the capabilities of cloud-computing for data management and statistical algorithm deployment, with system access via fully customisable web portals and mobile device applications. A pilot demonstrator will validate the use of the system for health and welfare monitoring with dairy cattle, creating alerts for farmers and their vets, for instance in relation to problems of fertility and lameness. A further pilot demonstrator will be implemented for horse breeders to prove transferability into additional applications.