Accurate and efficient thermal-infrared (IR) camera calibration is important for advancing computer vision research within the thermal modality. This paper presents an approach for geometrically ...calibrating individual and multiple cameras in both the thermal and visible modalities. The proposed technique can be used to correct for lens distortion and to simultaneously reference both visible and thermal-IR cameras to a single coordinate frame. The most popular existing approach for the geometric calibration of thermal cameras uses a printed chessboard heated by a flood lamp and is comparatively inaccurate and difficult to execute. Additionally, software toolkits provided for calibration either are unsuitable for this task or require substantial manual intervention. A new geometric mask with high thermal contrast and not requiring a flood lamp is presented as an alternative calibration pattern. Calibration points on the pattern are then accurately located using a clustering-based algorithm which utilizes the maximally stable extremal region detector. This algorithm is integrated into an automatic end-to-end system for calibrating single or multiple cameras. The evaluation shows that using the proposed mask achieves a mean reprojection error up to 78% lower than that using a heated chessboard. The effectiveness of the approach is further demonstrated by using it to calibrate two multiple-camera multiple-modality setups. Source code and binaries for the developed software are provided on the project Web site.
Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency ...allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle.
A large-scale, outdoor pervasive computing system uses static and animal-borne nodes to measure the state of a complex system comprising climate, soil, pasture, and animals. Agriculture faces many ...challenges, such as climate change, water shortages, labor shortages due to an aging urbanized population, and increased societal concern about issues such as animal welfare, food safety, and environmental impact. Humanity depends on agriculture and water for survival, so optimal, profitable, and sustainable use of our land and water resources is critical.
An ability of cattle to readily associate a non-aversive audio cue (conditioned stimulus) with an aversive but non-noxious electric shock (unconditioned stimulus) should enable virtual fences to ...control cattle in an ethical manner similar to conventional electric fencing. The first study was conducted to identify an effective audio cue. Audio (784
Hz tone) and shock (600
V, 250
mW) stimuli were delivered by remote control to GPS collars on five heifers to prevent access to an exclusion zone surrounding a feed trough. An audio cue was administered when the animal entered the exclusion zone, followed by a shock if the animal continued to proceed. There was an increase in the proportion of heifers responding favourably to the audio cue by turning, backing up or stopping in sessions 3 and 4 (73%) compared with sessions 1 and 2 (44%). This indicated that cattle associated the audio cue with the electric shock and learnt to avoid the trough. The main study examined whether cattle location can be controlled by an audio conditioned stimulus without the presence of a visual cue. Weeks 1 and 2 tested heifers’ learning of the association between an audio conditioned stimulus and an electric shock reinforcer. In week 3, the effect of dispensing with the conditioned stimulus was tested. Heifers were allocated to two treatments (
n
=
11). Treatment 1 received an audio cue and an electric shock on exclusion zone entry, as in the first 2 weeks. Treatment 2 received no audio cue and only an electric shock on exclusion zone entry. There was a difference in the behaviours shown in response to both the audio and shock stimuli between weeks 1 and 2, with more heifers turning in response to the audio cue in week 2 than in week 1. When the virtual fence was moved in week 2, 80% of animals ignored the first audio cue, but the proportion failing to respond to the second audio dropped to 46%, indicating that animals had learnt to avoid the electric shock by responding to the audio cue alone to remain within the virtual fence boundary. In week 3, heifers received significantly fewer shocks when a conditioned stimulus was used. There were no differences between treatments in scores for effectiveness of the fence, appropriateness of the stimulus and adverse responses. This study demonstrates that the appropriate use of an audio cue is an effective conditioned stimulus for virtual fencing of cattle.
Environmental Wireless Sensor Networks Corke, Peter; Wark, Tim; Jurdak, Raja ...
Proceedings of the IEEE,
11/2010, Letnik:
98, Številka:
11
Journal Article
Recenzirano
This paper is concerned with the application of wireless sensor network (WSN) technology to long-duration and large-scale environmental monitoring. The holy grail is a system that can be deployed and ...operated by domain specialists not engineers, but this remains some distance into the future. We present our views as to why this field has progressed less quickly than many envisaged it would over a decade ago. We use real examples taken from our own work in this field to illustrate the technological difficulties and challenges that are entailed in meeting end-user requirements for information gathering systems. Reliability and productivity are key concerns and influence the design choices for system hardware and software. We conclude with a discussion of long-term challenges for WSN technology in environmental monitoring and outline our vision of the future.
A wildfire which overran a sensor network site provided an opportunity (a natural experiment) to monitor short-term post-fire impacts (immediate and up to three months post-fire) in remnant eucalypt ...woodland and managed pasture plots. The magnitude of fire-induced changes in soil properties and soil microbial communities was determined by comparing (1) variation in fire-adapted eucalypt woodland vs. pasture grassland at the burnt site; (2) variation at the burnt woodland-pasture sites with variation at two unburnt woodland-pasture sites in the same locality; and (3) temporal variation pre- and post-fire. In the eucalypt woodland, soil ammonium, pH and ROC content increased post-fire, while in the pasture soil, soil nitrate increased post-fire and became the dominant soluble N pool. However, apart from distinct changes in N pools, the magnitude of change in most soil properties was small when compared to the unburnt sites. At the burnt site, bacterial and fungal community structure showed significant temporal shifts between pre- and post-fire periods which were associated with changes in soil nutrients, especially N pools. In contrast, microbial communities at the unburnt sites showed little temporal change over the same period. Bacterial community composition at the burnt site also changed dramatically post-fire in terms of abundance and diversity, with positive impacts on abundance of phyla such as Actinobacteria, Proteobacteria and Firmicutes. Large and rapid changes in soil bacterial community composition occurred in the fire-adapted woodland plot compared to the pasture soil, which may be a reflection of differences in vegetation composition and fuel loading. Given the rapid yet differential response in contrasting land uses, identification of key soil bacterial groups may be useful in assessing recovery of fire-adapted ecosystems, especially as wildfire frequency is predicted to increase with global climate change.
•Natural experiment compared burnt vs unburnt sites to determine wildfire impacts.•Contrasting effects in native woodland vs managed pasture soils.•Soil NH4 increased post-fire in woodland soil whilst NO3 increased in pasture soil.•Rapid change with greater diversity in woodland bacterial community composition.
The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various ...objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.
Summary
Network and multivariate statistical analyses were performed to determine interactions between bacterial and fungal community terminal restriction length polymorphisms as well as soil ...properties in paired woodland and pasture sites. Canonical correspondence analysis (CCA) revealed that shifts in woodland community composition correlated with soil dissolved organic carbon, while changes in pasture community composition correlated with moisture, nitrogen and phosphorus. Weighted correlation network analysis detected two distinct microbial modules per land use. Bacterial and fungal ribotypes did not group separately, rather all modules comprised of both bacterial and fungal ribotypes. Woodland modules had a similar fungal : bacterial ribotype ratio, while in the pasture, one module was fungal dominated. There was no correspondence between pasture and woodland modules in their ribotype composition. The modules had different relationships to soil variables, and these contrasts were not detected without the use of network analysis. This study demonstrated that fungi and bacteria, components of the soil microbial communities usually treated as separate functional groups as in a CCA approach, were co‐correlated and formed distinct associations in these adjacent habitats. Understanding these distinct modular associations may shed more light on their niche space in the soil environment, and allow a more realistic description of soil microbial ecology and function.
Farming the Web of Things Taylor, Kerry; Griffith, Colin; Lefort, Laurent ...
IEEE intelligent systems,
2013-Nov.-Dec., 2013-11-00, 20131101, Letnik:
28, Številka:
6
Journal Article
Recenzirano
Here, a Web of Things case study for agriculture focuses on an experimental smart farm that uses a range of environmental sensors and livestock monitoring technologies. An ontology-enabled ...architecture that permits personal alert specification was applied on the farm and the results analyzed; the observations are published as a linked data cube, which supports longer-term analysis and data sharing from a local to national scale. This case study highlights the business opportunities for such technology for agriculture in the context of a national broadband rollout.
Combining multiple proximal sensors within a wireless sensor network (WSN) enhances our capacity to monitor vegetation, compared to using a single sensor or non-networked setup. Data from sensors ...with different spatial and temporal characteristics can provide complementary information. For example, point-based sensors such as multispectral sensors which monitor at high temporal frequency but, at a single point, can be complemented by array-based sensors such as digital cameras which have greater spatial resolution but may only gather data at infrequent intervals. In this article we describe the successful deployment of a prototype system for using multiple proximal sensors (multispectral sensors and digital cameras) for monitoring pastures. We show that there are many technical issues involved in such a deployment, and we share insights relevant for other researchers who may consider using WSNs for an operational deployment for pasture monitoring under often difficult environmental conditions. Although the sensors and infrastructure are important, we found that other issues arise and that an end-to-end workflow is an essential part of effectively capturing, processing and managing the data from a WSN. Our deployment highlights the importance of testing and ongoing monitoring of the entire workflow to ensure the quality of data captured. We demonstrate that the combination of different sensors enhances our ability to identify sensor problems necessary to collect accurate data for pasture monitoring.
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