- What exactly are farm management systems?
- CowControl collar system monitors eating and rumination habits
- CattleEye system detects lameness in dairy cows
- Moonsyst monitors livestock wellbeing from within the cow
With a projected worldwide population of 9.7 billion by the time we get to 2050, agricultural production will need to grow by 70 per cent at the very least in order to be able to feed everyone. So, the pressure for farmers to produce ever larger quantities of food is mounting and putting our planet under more and more strain. Meeting these increasing demands will require the agricultural sector – and livestock farming in particular – to undergo widespread automation. This could include agricultural robots, sensor technology, autonomous tractors, farm management information systems (FMIS) and other advanced technologies, which – especially when combined – could help livestock farmers keep up with the ever growing demand for food, and vastly improve productivity, sustainability, and profitability.
The worldwide livestock monitoring market size was valued at $4.62 billion in 2021 and is expected to expand at a compound annual growth rate (CAGR) of 17.63 per cent between 2022 and 2030. The growth of the market can be attributed to the upsurge in cattle population, in combination with the increasing implementation of advanced monitoring technology.
Grand View Research
What exactly are farm management information systems?
Livestock farmers all over the world are increasingly making use of advanced farm management information systems (FMIS) which encompass hardware such as neck collars, ear tags, and rumen bolus-based systems used to gather and analyse sensor-generated information. This valuable data enables farmers to know all there is to know about their animals’ wellbeing. And this knowledge is critical, as healthy, happy cows produce the best quality milk and meat. To be able to closely monitor an entire group of these animals – and remember the status of each individual one – is no easy feat. And particularly now that labour becomes scarcer, the level of attention needed to keep a close eye is becoming a real challenge. FMIS systems, particularly those which have algorithms incorporated, can make all kinds of useful forecasts, detect diseases and conditions such as lameness, and assess general overall health.
Systems that use machine learning technology will deliver the most benefits, as these will be able to learn, analyse, adapt, and draw conclusions from patterns in the information gathered. According to Grand View Research, the worldwide livestock monitoring market size was valued at $4.62 billion in 2021 and is expected to expand at a compound annual growth rate (CAGR) of 17.63 per cent between 2022 and 2030. The expansion of the market can be attributed to the upsurge in cattle population, in combination with the increasing implementation of advanced monitoring technology. Animal agriculture is expected to experience a huge revolution as a result of smart IoT sensor technology.
CowControl collar system monitors eating and rumination habits
Cow health assessment is based on a combination of various parameters, and the Nedap CowControl collar system – which includes SmartTags – enables farmers to monitor their animal’s position, activities like eating, standing still, lying, walking and rumination habits, and inactive behaviour. It also tracks signs of heat – such as increased activity, sniffing, mounting behaviour, and chin resting – to help determine their optimal insemination moment. The system compares all the various behavioural and health indicators with the standards for optimum health, fertility, and nutritional status. Other factors that are included in the assessment are previous behaviour of each individual animal, as well group behaviour and any abnormalities or changes. As soon as any unusual behaviour is detected, the system sends out alerts. The most recent addition to the system is Nedap’s augmented reality (AR) application, which brings the farmer’s real world and digital information together. AR enables the farmer to perform and register actions via voice commands or hand gestures, and helps to enrich a farmer’s field of view with relevant cow data at the right time and place.
CattleEye system detects lameness in dairy cows
CattleEye, the first hardware-independent autonomous livestock monitoring platform in the world, was created by Terry Canning, a dairy farmer’s son from Northern Ireland, and Adam Askew, a senior architect with more than 10 years experience in deep learning image analytics. The platform uses a low-cost security camera combined with deep learning video analytics to capture and analyse video footage to provide insights into cattle health and behaviour. The camera is fitted above the exit of milking parlours, eliminating the need for pedometers or collars. CattleEye’s machine vision AI enables the autonomous identification of every individual animal, measures gait, and applies mobility scores. It then analyses and detects locomotion deviations in individual dairy cows, which could be indicative of lameness and would require intervention. Insights can either be transmitted to the existing herd management system or a smartphone, tablet, or PC. With a combined experience of forty years in healthcare image analytics powered by deep learning, Adam and his team continue to work hard on creating systems that offer farmers access to the very latest in AI powered video analytics to improve the health and wellbeing of their livestock.
Moonsyst monitors livestock wellbeing from within the cow
A partnership between Hungary-based Moonsyst and Modus IoT has resulted in the development of Moonsyst International Ltd, a company that creates the innovative Smart Rumen Monitoring System. The system gathers information from within the cows, enabling farmers to monitor health conditions in real time and enabling improvements in productivity and sustainability. The system makes use of a rumen bolus – a capsule that is either swallowed or inserted into the animal’s stomach or rumen and settles in the reticulum where it remains for the duration of its life. It contains a sensor and a transmitter that connect to a cloud-based data processing application via a mobile app. The bolus measures and monitors behavioural, physiological, and chemical data, such as eating behaviours and movement, body core temperature, and any changes that might indicate health problems. In the case of prolonged elevated temperature change, for instance, an alert is sent to the farmer to indicate the animal requires attention. The Moonsyst system can also identify heats, and after a confirmed insemination, the status of the cow automatically changes to ‘inseminated’. Following a positive pregnancy check, the status of the cow changes to ‘pregnant’, after which the system continues to monitor the animal’s condition until calving is completed, all the while measuring and reporting on the cow’s and calf’s wellbeing.
Final thoughts
The versatility of livestock – with meat and milk providing excellent sources of vitamins, minerals, and protein – makes it central to the survival of millions of people. But farming animals for food is increasingly raising all manner of complex questions. And the worldwide transition to a modern, competitive, and resource-efficient economy – with environmental impact and animal wellbeing becoming increasingly critical factors – poses numerous challenges for (the younger generations of) livestock farmers. Remaining profitable while complying with new worldwide agricultural norms and guidelines requires ever larger farms and necessitates the implementation of advanced technologies. Thankfully, more and more agritech companies are developing affordable monitoring and management technologies to improve livestock sector practices, help farmers become more efficient, productive, and sustainable, and pose less risk to animal and human health.
