Horticultural production without using herbicides and with minimal till is growing in popularity. However many tasks in these systems such as hoeing weeds or washing away pests are labour intensive and some tractor mounted tools exist that can automate these tasks. It is probable that for many years to come humans and robots will work together(Hybrid Working) in fields. Hybrid working with both humans and robots in a field are unproven. This project will integrate automated animal/human detection systems and develop standard operating procedures to ensure that humans and robots can work safely together in horticulture both commercially and community based such as in allotments.

This project will create an automatic method of downloading data from rumen bolus on farms and integrating it to other management applications where each cow's data will be stored in a published interoperable data schema so it can be integrated with content of other datasets about the cow. The project will improve the day to day management of cows and extend their lives by allowing better nutrition and attention to healthcare details. The aim is to individualise the cow data as she is kept in an increasingly larger herds and to improve cow health and welfare with high technology monitoring.

This project tests the concept of integrating data from multiuple sensors and integratiung the data to provide management prompts to farmers who at present typically feel overloaded with data. Data from a combination of existing wireless telemetric sensors in and on the cow will be combined with data from sensors in the milking systems to determine optimal nutrition and fertility status throughout the cow's life working life and offer management decisions to the farmer to improve milk yields and reduce nitrate, ammonia and methane emissions from the cow. New models will be developed based on combining existing models into an integrated system for cow management. The aim is to better target inputs into the cow to produce more milk from less resources, the system will be suitable for all types of farm system whether organic or conventional. The project addresses the frequent complaint from farmers that there is too much data requiring interpretation for which they don't have time.

An investigation to map wireless sensor signal strength in applications where signals are attenuated by soil, water and tissue.