Bovine respiratory disease (BRD), and resulting pneumonia caused by viral and/or bacterial pathogens, is the most common disease affecting the cattle industry globally. Calf pneumonia is a cause of major economic loss, affecting over a million animals across the UK and costing the UK dairy industry ~£60-80million pa. While BRD can affect up to 50% of cattle, with resulting fatalities of up to 10%, half of all cases are often not detected or treated at the time of infection, potentially resulting in a lifelong reduction in productivity and costing up to an estimated £1k per infected animal. Detection of BRD/pneumonia in calves is currently through clinical signs, usually first identified, and often treated, by the farmer with the application of anti-inflammatories and/or antibiotics. However, many of these symptoms can be subtle, or an indication of other diseases. Early stage diagnosis of BRD in calves provides a means for early intervention to effectively treat the disease, and limit its spread, reducing the use of antibiotics, improving animal welfare, and increasing lifelong potential milk yields by as much as 8%. The innovation delivered by this project is a fast response capnometer for early stage diagnosis and management of BRD/pneumonia respiratory conditions. This technique has been successfully deployed for use in diagnosis/ management of chronic respiratory conditions in humans, supported by previous input from team members in this project. Competitive techniques include remote temperature sensing and behaviour monitoring, neither of which are specific to respiratory disease but could be complementary to the proposed sensor system. This project draws on Albasense's novel fast-response solid state gas sensor technology; Wideblue's electro-mechanical systems design and integration; Paragon's veterinary expertise; and McCaskie's knowledge of innovative technologies in the sector, to address this key challenge of the dairy industry. At a time when skilled labour is at an all-time low and input costs high, improving productivity and margins for dairy farmers is critical to sustaining the UK industry and dairy supply chain. The adoption of novel sensing technologies can add value beyond the mere financial, for overstretched and under pressure farmers.

The intensification of dairy farming has resulted in an increasing disconnect between the vision that consumers have of a dairy farm and the reality. As a consequence, when consumers are provided with a partial picture of the practices employed on dairy farms, the over-riding conclusion is that current farm practices do not protect the environment; 1 in 3 adults believe that the farming and production of dairy foods significantly contributes to overall climate change. The farms and dairy companies able to clearly communicate and provide evidence of the positive impact that their operations have on both the local and global environment are more likely to remain not only economically viable but are able to gain access to higher value markets. The requirement to ensure the sustainability of the dairy supply chain is to establish a validated standard framework enabling the certification of best practices for rewarding production practices minimise the detrimental impact on climate. In the UK, it is currently estimated that 10% of the country's total GHG emissions come from agriculture, (46.3 Mt CO2e pa). The main GHG from agriculture is methane from ruminants (56%), followed by nitrous oxide from fertilisers (31%). The most important greenhouse gas in farming is methane predominantly from ruminants which has a GHG impact 34 times that of CO2\. Globally cattle contributes to 13% of methane emissions. The dairy sector has begun to address the pressing need to reduce methane emissions through genetics and with the use of feed additives. However, presently, there is no industry standard for methane measurement that can independently quantify the mass of methane produced on an operational farm, driving a near-term need for reliable cost-effective measurement methods. Research farms have deployed automated feeder systems with aspirated methane measurement devices e.g. Green-feed, however these are prohibitively expensive (~£70k per unit), a significant barrier to widespread adoption. The project aims to deliver a low-cost, robust methane sensor which can be rapidly retrofitted to existing farm equipment e.g. milking robots with minimal installation cost to increase the adoption of GHG measurement equipment. The approach is compatible with creating sensor networks for infield deployment to provide real-time measurement with higher granularity over current remote sensing survey approaches. The power harvesting solution eliminates the need for both hard wiring (which is not practical or cost effective) and battery power, unacceptable due to the need for regular changes and also environmentally unacceptable.

Methane is a significant contributor to global warming so reducing methane emissions, particularly from oil and gas operations, is among the most cost-effective, impactful actions governments can take to achieve climate goals. Preventing methane leakage impacts economic productivity and worker safety too. Large-site leak detection requires reliable cost-effective distributed sensors. Methane leakage is also an issue for several other industries. Distributed methane sensor networks would improve measurement regularity and granularity over current remote sensing survey approaches. However, hard wiring is not practical or cost effective and battery power is unacceptable due to the need for regular changes requiring engineers working in hazardous areas at great expense. The sustainability challenge of additional travel associated with device maintenance and disposal of used batteries in the millions is also environmentally unacceptable. Worker safety monitoring with lower-cost portable methane detectors requires bulky, rechargeable battery-powered devices that the industry is seeking to avoid for operational and environmental reasons. We combine and optimise Albasense's novel ultra-low-power methane sensor technology with Lightricity's world-leading high-efficiency PV technology and power management IP/expertise to deliver a world-first autonomous battery-free, light-powered long-range wireless methane sensor communicating via LoRa, minimising on-site gateway infrastructure. This will operate indoors and outdoors providing the granularity of measurement to allow much more widespread and cost-effective sensing in multiple applications. We target fixed sensor and wearable badge formats for use-case versatility. Device performance will be demonstrated over a representative range of methane levels and environmental conditions of relevance to projected use-cases with input from users and gas detector manufacturing companies.