Method for selection of pig manure processing technologies

E. Shalavina*, A. Briukhanov, R. Uvarov, E. Vasilev

Institute for Engineering and Environmental Problems in Agricultural Production – IEEP, Department of Environmental Engineering of Agricultural Production, 3, Filtrovskoje Shosse, p.o. Tiarlevo, Saint Petersburg-Pavlovsk RU196625, Russia.
*Correspondence: shalavinaev@mail.ru

Abstract:

The criteria, which take into account both economic and environmental indicators, were suggested for assessment of technologies and selection of the most reasonable solution. The method of Pareto optimization was applied. Technologies suited for the North-West Russia were considered to design a mathematical model and to obtain the required indicators for the criteria calculation. The technology of multi-stage processing of pig manure with cyclic sedimentation tanks was studied in more detail based on a separate, specially designed three-level mathematical model. The objective function was the eco-economic index of nitrogen, which is the ratio between the economic benefit from the marketed yield increment and the costs of nutrients retention in the organic fertilizers applied to soil under the harvested crop yield. The resulting simulation data were substantiated by experimental studies. A mathematical model and an algorithm for selecting the best-suited technology were designed. As the calculation process involved a large bulk of data, the WEB programming was used. Simulation results demonstrated 90% accurate choice of technology. The designed model was tested for the conditions of a pig complex in Leningrad Region with the manure output of 150 t per day and no own farmland for organic fertilizer application. Calculations proved the economic and ecological effectiveness of the multi-stage processing of pig manure: operating costs per one ton of produced organic fertilizer were reduced 1.8 times, fuel costs – 1.4 times and labour costs – 3.3 times. The chosen technology also featured higher ecological safety coefficient. Estimated ecological and economic effect of introduction of this technology amounted to 5936 thousand roubles per year.

Key words:

Technical and software solutions for autonomous unmanned aerial vehicle (UAV) navigation in case of unavailable GPS signal

M. Dlouhy¹, J. Lev² and M. Kroulik¹*

¹Czech University of Life Sciences Prague, Faculty of Engineering, Department of Agricultural Machines, Kamýcká 129, CZ165 21 Prague 6, Czech Republic
²Czech University of Life Sciences Prague, Faculty of Engineering, Department of Physics, Kamýcká 129, CZ165 21 Prague 6, Czech Republic
*Correspondence: kroulik@tf.czu.cz

Abstract:

The article presents autonomous navigation for Unmanned Aerial Vehicles (UAV) without GPS support flying in extremely low altitudes (1.5 m – 2.5 m). Solution via visual navigation as an alternative to missing GPS position was proposed. MSER (Maximally stable extremal regions) was used as a navigation algorithm for detection of navigations objects. While GPS is useful for waypoints specification there are scenarios where GPS has unreliable signal (orchards) or is not available at all (indoor machinery halls or greenhouses). For that reason existing installed camera which is already needed for the task of inspection was used. The navigation algorithm was tested in two scenarios. The first experiment was done with dashed line marked on the floor of the hall. 8-loop testing track was created approximately 10 meters long so it was possible to fly it several times. Then outdoor experiments were performed on the university campus and park roads.
One of the discoveries was that MSER algorithm, proposed for finding correspondences between images, is possible to run in real-time. High reliability of the navigation algorithm was found during the indoor testing. The incorrect detection of the dashed line was found only in 1% of cases and those failures did not cause failure of navigation.
Although outdoor road recognition is difficult in general due to various surfaces and smoothness, MSER was able to find suitable candidates. When the UAV was fed with the parameter of road width it could verify that information with estimated distance and camera pose to accept or reject the detected pattern. The road was successfully recognized in 40% cases. Similar to the indoor algorithm in the case of navigation failure navigation along the absolute trajectory (line) was used.

Key words:

algorithm, machine vision, maximally stable extremal regions, robot