Smart Dairy Cattle Farming and In-Heat Detection through the Internet of Things (IoT)

The Internet of Things (IoT) technology has been being revolutionized in various aspects of agriculture around the world ever since. Its application has already found its success in some countries. On the contrary, this technology has yet to find its substantial breakthrough in the Philippines. This study shows the application of IoT in improving the detection efficiency of standing-heat behaviors of cows through automated detection using Pan-tilt-zoom cameras and a Python-driven Web Application. The dimensions of the barn were measured, and the Cameras' Field of Views (FOVs) were pre-calculated for the strategic positions of the cameras atop of the cowshed. The program detects the cows and any estrus events through the surveillance cameras. The results will be sent to the cloud server to display on the web application for analysis. The web app can allow updates on cow information, inseminations, pregnancy, and calving records, estimate travel time from the user's geolocation to the farm, provide live monitoring and remote camera accessibility and control through the cameras and deliver reliable cross-platform push-notification and call alerts on the user's device(s) whenever an estrus event is detected. Based on the results, the program performed satisfactorily at 50% detection efficiency

EIP-AGRI Focus Group : Precision farming

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The impact of agricultural activities on water quality: a case for collaborative catchment-scale management using integrated wireless sensor networks

The challenge of improving water quality is a growing global concern, typified by the European Commission Water Framework Directive and the United States Clean Water Act. The main drivers of poor water quality are economics, poor water management, agricultural practices and urban development. This paper reviews the extensive role of non-point sources, in particular the outdated agricultural practices, with respect to nutrient and contaminant contributions. Water quality monitoring (WQM) is currently undertaken through a number of data acquisition methods from grab sampling to satellite based remote sensing of water bodies. Based on the surveyed sampling methods and their numerous limitations, it is proposed that wireless sensor networks (WSNs), despite their own limitations, are still very attractive and effective for real-time spatio-temporal data collection for WQM applications. WSNs have been employed for WQM of surface and ground water and catchments, and have been fundamental in advancing the knowledge of contaminants trends through their high resolution observations. However, these applications have yet to explore the implementation and impact of this technology for management and control decisions, to minimize and prevent individual stakeholder’s contributions, in an autonomous and dynamic manner. Here, the potential of WSN-controlled agricultural activities and different environmental compartments for integrated water quality management is presented and limitations of WSN in agriculture and WQM are identified. Finally, a case for collaborative networks at catchment scale is proposed for enabling cooperation among individually networked activities/stakeholders (farming activities, water bodies) for integrated water quality monitoring, control and management

The Innovative Techniques in Animal Husbandry

Technology is developing rapidly. In this development, the transfer of computer systems and software to the application has made an important contribution. Technologic instruments made farmers can work more comfortable and increased animal production efficiency and profitability. Therefore, technologic developments are the main research area for animal productivity and sustainability. Many technologic equipment and tools made animal husbandry easier and comfortable. Especially management decisions and applications are effected highly ratio with this rapid development. In animal husbandry management decisions that need to be done daily are configured according to the correctness of the decisions to be made. At this point, smart systems give many opportunities to farmers. Milking, feeding, environmental control, reproductive performance constitute everyday jobs most affected by correct management decisions. Human errors in this works and decisions made big effect on last product quality and profitability are not able to be risked. This chapter deal with valuable information on the latest challenges and key innovations affecting the animal husbandry. Also, innovative approaches and applications for animal husbandry are tried to be summarized with detail latest research results

Ground and Aerial Robots for Agricultural Production: Opportunities and Challenges

Crop and animal production techniques have changed significantly over the last century. In the early 1900s, animal power was replaced by tractor power that resulted in tremendous improvements in field productivity, which subsequently laid foundation for mechanized agriculture. While precision agriculture has enabled site-specific management of crop inputs for improved yields and quality, precision livestock farming has boosted efficiencies in animal and dairy industries. By 2020, highly automated systems are employed in crop and animal agriculture to increase input efficiency and agricultural output with reduced adverse impact on the environment. Ground and aerial robots combined with artificial intelligence (AI) techniques have potential to tackle the rising food, fiber, and fuel demands of the rapidly growing population that is slated to be around 10 billion by the year 2050. This Issue Paper presents opportunities provided by ground and aerial robots for improved crop and animal production, and the challenges that could potentially limit their progress and adoption. A summary of enabling factors that could drive the deployment and adoption of robots in agriculture is also presented along with some insights into the training needs of the workforce who will be involved in the next-generation agriculture

A comparison of low-cost techniques for three-dimensional animal body measurement in livestock buildings

Data about health and development of animals are still now mostly collected through manual measurements or visual observations but these kinds of methods of collecting data are causes of several problems. Alternatively, optical sensing techniques can be implemented in order to overcome limitations arising from manual contact measurements. The present research discusses metrological analysis of Structure from motion (SfM) photogrammetry approach, low-cost LiDAR scanning and Microsoft Kinect v1 depth camera to three- dimensional animal body measurement, with specific reference to pigs. Analyses were carried out on fiberglass model to get rid of animal movements. Scans were captured based on a segmented approach, where different portion of the body have been imaged during different frames acquisition tasks. The obtained results demonstrate the high potential of 3D Kinect. LiDAR show a higher RMS value respect to Kinect and SfM most probably due to the collection approach based on single profiles rather than on surfaces. Anyway, the RMS of relative noise ranges between 0.7 and 4 mm, showing a high accuracy of reconstructions even for the others techniques