The Internet of Things enhancing animal welfare and farm operational efficiency.

The growth in wirelessly enabled sensor network technologies has enabled the low cost deployment of sensor platforms with applications in a range of sectors and communities. In the agricultural domain such sensors have been the foundation for the creation of decision support tools that enhance farm operational efficiency. This Research Reflection illustrates how these advances are assisting dairy farmers to optimise performance and illustrates where emerging sensor technology can offer additional benefits. One of the early applications for sensor technology at an individual animal level was the accurate identification of cattle entering into heat (oestrus) to increase the rate of successful pregnancies and thus optimise milk yield per animal. This was achieved through the use of activity monitoring collars and leg tags. Additional information relating to the behaviour of the cattle, namely the time spent eating and ruminating, was subsequently derived from collars giving further insights of economic value into the wellbeing of the animal, thus an enhanced range of welfare related services have been provisioned. The integration of the information from neck-mounted collars with the compositional analysis data of milk measured at a robotic milking station facilitates the early diagnosis of specific illnesses such as mastitis. The combination of different data streams also serves to eliminate the generation of false alarms, improving the decision making capability. The principle of integrating more data streams from deployed on-farm systems, for example, with feed composition data measured at the point of delivery using instrumented feeding wagons, supports the optimisation of feeding strategies and identification of the most productive animals. Optimised feeding strategies reduce operational costs and minimise waste whilst ensuring high welfare standards. These IoT-inspired solutions, made possible through Internet-enabled cloud data exchange, have the potential to make a major impact within farming practices. This paper gives illustrative examples and considers where new sensor technology from the automotive industry may also have a role.

Measurement of spatial and temporal variation in volatile hazardous air pollutants in Tacoma, Washington, using a mobile membrane introduction mass spectrometry (MIMS) system.

The objective of this study was to use membrane introduction mass spectrometry (MIMS), implemented on a mobile platform, in order to provide real-time, fine-scale, temporally and spatially resolved measurements of several hazardous air pollutants. This work is important because there is now substantial evidence that fine-scale spatial and temporal variations of air pollutant concentrations are important determinants of exposure to air pollution and adverse health outcomes. The study took place in Tacoma, WA during periods of impaired air quality in the winter and summer of 2008 and 2009. Levels of fine particles were higher in winter compared to summer, and were spatially uniform across the study area. Concentrations of vapor phase pollutants measured by membrane introduction mass spectrometry (MIMS), notably benzene and toluene, had relatively uniform spatial distributions at night, but exhibited substantial spatial variation during the day-daytime levels were up to 3-fold higher at traffic-impacted locations compared to a reference site. Although no direct side-by-side comparison was made between the MIMS system and traditional fixed site monitors, the MIMS system typically reported higher concentrations of specific VOCs, particularly benzene, ethylbenzene and naphthalene, compared to annual average concentrations obtained from SUMA canisters and gas chromatographic analysis at the fixed sites.

The national ambient air monitoring strategy: rethinking the role of national networks.

A current re-engineering of the United States routine ambient monitoring networks intended to improve the balance in addressing both regulatory and scientific objectives is addressed in this paper. Key attributes of these network modifications include the addition of collocated instruments to produce multiple pollutant characterizations across a range of representative urban and rural locations in a new network referred to as the National Core Monitoring Network (NCore). The NCore parameters include carbon monoxide (CO), sulfur dioxide (SO2), reactive nitrogen (NOy), ozone (O3), and ammonia (NH3) gases and the major fine particulate matter (PM2.5) aerosol components (ions, elemental and organic carbon fractions, and trace metals). The addition of trace gas instruments, deployed at existing chemical speciation sites and designed to capture concentrations well below levels of national air quality standards, is intended to support both long-term epidemiological studies and regional-scale air quality model evaluation. In addition to designing the multiple pollutant NCore network, steps were taken to assess the current networks on the basis of spatial coverage and redundancy criteria, and mechanisms were developed to facilitate incorporation of continuously operating particulate matter instruments.