Cat and Mouse Based Task Optimization Model for Optimized Data Collection in Smart Agriculture

Data collection from agricultural fields is tiring and requires novel methodologies to produce reliable outcomes. The combination of edge and wireless sensor networks (WSN) for smart farming enabled the efficient collection of data from remote fields to a vast extent. Adopting an optimization algorithm to achieve the data collection task is prioritized in the proposed work, and a new and effective data collection framework is proposed. The proposed framework initially collects the data from the agricultural fields via sensors and then transmits it to the edge server. The path between the sensors and the edge server is optimally obtained using the cat and mouse based task optimization (CMTO) model. The sensed data are transmitted through the optimal route, and then the edge server obtains and evaluates the data based on the data quality metrics such as precision, correctness, completeness and reliability. The valid data are then identified and transferred to the cloud servers for storage. The simulation of the work is done in Python platform and evaluated using the crop recommender dataset. The evaluations proved the method's efficacy compared to the existing state-of-the-art algorithms. The proposed work also provided upto 12.5% of improvement in terms of energy consumption, 7.14% of improvement in terms of communication latency, 4% of improvement in terms of execution cost, 2.27% of improvement in terms of completeness, 1.12% of improvement in terms of precision, 9.52% of improvement in terms of correctness, and 3.37% of improvement in terms of reliability

Investigation of airflow around buildings using Large-Eddy Simulations for Unmanned Aircraft Systems applications

The ever-increasing demand for Unmanned Aircraft Systems (UAS) has led to the desire for integrating them into spaces in close proximity of humans like dense urban spaces, a reality previously thought of as inconceivable. One of the main concerns to be addressed before its widespread adoption is safety, especially in areas of operation adjacent to structures like buildings. This work investigates the effect of building geometries on the flow field in a simplified urban setup consisting of an isolated building to predict their potential impacts on UAS operations. Unanticipated wind gusts or turbulent flow conditions prevalent around various structures constitute a significant challenge for UAS operations in urban environments. We use Large-Eddy Simulation to better understand the unsteady and highly coherent turbulent flow structures produced by buildings in neutral atmospheric boundary layer flow. Furthermore, we also demonstrate a non-intrusive machine learning methodology to predict flow fields to augment safe wind-aware navigation systems for Unmanned Aerial Vehicles as a first step towards safely integrating UAS into existing aerial infrastructure.Mechanical and Aerospace Engineerin

Nanocomposites photocatalysis application for the purification of phenols and real olive mill wastewater through a sequential process

In this study, a synthetic phenol solution of water and raw olive mill wastewater (OMW) were considered to achieve purification of the aqueous streams from pollutants. Only OMW was initially submitted to a coagulation/flocculation process, to reduce the turbidity, phenols, and chemical oxygen demand (COD). This first treatment appeared to be mandatory in order to remove solids from wastewater, allowing the successive use of laboratory-made core-shell nanocomposites. In detail, the optimal coagulant concentration, i.e., chitosan, was 500 mg/L, allowing a reduction of the turbidity and the COD value by 90% and 33%, respectively. After this, phenol wastewater was tested for photocatalysis and then OMW was treated by employing the laboratory-made nanocomposites in a photoreactor equipped with visible light sources and using optimal catalyst concentrations, which allowed for an additional 45% reduction of the COD of the OMW. In addition to this, the effect of the operating temperature was investigated on the photocatalytic process, and suitable kinetic models proposed

Optimization of Membrane Electrode Assembly of PEM Fuel Cell by Response Surface Method

The membrane electrode assembly (MEA) plays an important role in the proton exchange membrane fuel cell (PEMFC) performance. Typically, the structure comprises of a polymer electrolyte membrane sandwiched by agglomerate catalyst layers at the anode and cathode. Optimization of various parameters in the design of MEA is, thus, essential for reducing cost and material usage, while improving cell performance. In this paper, optimization of MEA is performed using a validated two-phase PEMFC numerical model. Key MEA parameters affecting the performance of a single PEMFC are determined from sensitivity analysis and are optimized using the response surface method (RSM). The optimization is carried out at two different operating voltages. The results show that membrane thickness and membrane protonic conductivity coefficient are the most significant parameters influencing cell performance. Notably, at higher voltage (0.8 V per cell), the current density can be improved by up to 40% while, at a lower voltage (0.6 V per cell), the current density may be doubled. The results presented can be of importance for fuel cell engineers to improve the stack performance and expedite the commercialization

Multi-response optimization of coagulation and flocculation of olive mill wastewater. Statistical approach

Olive oil production is one of the important industrial sectors within the agro-food framework of the Mediterranean region, economically important to the people working in this sector, although there is also a threat to the environment due to residues. The main wastes of the olive oil extraction process are olive mill wastewater (OMW) and olive husks which also require proper treatment before dismissal. In this research work, the main goal is to introduce grey relational analysis, a technique for multi-response optimization, to the coagulation and flocculation process of OMW to select the optimum coagulant dosage. The coagulation and flocculation process was carried out by adding aluminum sulfate (Alum) to the waste stream in different dosages, starting from 100 to 2000 mg/L. In previous research work, optimization of this process on OMW was briefly discussed, but there is no literature available that reports the optimal coagulant dosage verified through the grey relational analysis method; therefore, this method was applied for selecting the best operating conditions for lowering a combination of multi-responses such as chemical oxygen demand (COD), total organic carbon (TOC), total phenols and turbidity. From the analysis, the 600 mg/L coagulant dosage appears to be top ranked, which obtained a higher grey relational grade. The implementation of statistical techniques in OMW treatment can enhance the efficiency of this process, which in turn supports the preparation of waste streams for further purification processes in a sustainable way

Pre-treatment processes optimization for the purification of olive mill wastewater through a pilot-scale membrane plant

The reported work deals with the evaluation of two different pre-treatment processes performances for the purification of a real olive mill wastewater. The wastewater was from an oil mill placed in the South of Italy and presents high Chemical Oxygen Demand (COD), Total Organic Carbon (TOC) and phenols concentrations, besides other organic pollutants, an acid pH and brown colour. Therefore, this complex wastewater resulted in low- biodegradable and difficult to be treated by a solely process. To this aim, the present work will evaluate optimal operating parameters of coagulation-flocculation and photocatalysis pre-treatments to achieve suitable physical-chemical properties of the effluent, before the membrane treatment in a pilot-scale plant. In detail, the wastewater was firstly treated with an organic coagulant (chitosan) and then a photocatalytic step follows before the more efficient integrated membrane process. After the photocatalytic process, the COD, TOC and Phenols concentrations decreased to up 42 %, 38 % and 36 %, respectively, in comparison with the initial values. Subsequently, a series of four separation processes (ultrafiltration, nanofiltration and reverse osmosis) was performed and almost the total initial COD, TOC and phenols concentrations were removed

Cr(VI) removal by chitosan-magnetite nano-composite in aqueous solution

The production of functionalized nano-composites represents an important research activity in the environmental remediation field. The use of iron-based nano-particles (IBNs) supported on bio-polymer matrix might lead to the development of active nano-materials characterized by a notable eco-compatibility. Chitosan is a biodegradable biopolymer that can be effectively used to produce active nano-composites with IBNs. In this study, a chitosan-magnetite nano-composite was produced in the laboratory and used in batch experimental tests for the removal of Hexavalent Chromium, Cr(VI), in aqueous solutions. Cr(VI) is considered one of the most toxic compounds present in the Mediterranean Area due to its carcinogenic and mutagenic characteristics, besides its notable solubility and mobility in the environment. The most effective way for the remediation of Cr(VI)-polluted groundwater is represented by the combination of chemical reduction and co-precipitation processes, generating Cr(III) species, characterized by very low toxicity and solubility in comparison to Cr(VI) ones. The synthesized nano-composite was used in batch lab-scale reactors and the kinetics of the process was studied varying the initial nano-composite concentration (0.25, 0.5, 0.75, 1 g/L) at fixed Cr(VI) initial concentration (20 mg/L). In addition, the initial pH influence on the Cr(VI) removal efficiency was analyzed in the range 3-7

Remote Sensing and GIS Techniques for Evaluation of Groundwater Quality in Municipal Corporation of Hyderabad (Zone-V), India

Groundwater quality in Hyderabad has special significance and needs great attention of all concerned since it is the major alternate source of domestic, industrial and drinking water supply. The present study monitors the ground water quality, relates it to the land use / land cover and maps such quality using Remote sensing and GIS techniques for a part of Hyderabad metropolis. Thematic maps for the study are prepared by visual interpretation of SOI toposheets and linearly enhanced fused data of IRS-ID PAN and LISS-III imagery on 1:50,000 scale using AutoCAD and ARC/INFO software. Physico-chemical analysis data of the groundwater samples collected at predetermined locations forms the attribute database for the study, based on which, spatial distribution maps of major water quality parameters are prepared using curve fitting method in Arc View GIS software. Water Quality Index (WQI) was then calculated to find the suitability of water for drinking purpose. The overall view of the water quality index of the present study area revealed that most of the study area with > 50 standard rating of water quality index exhibited poor, very poor and unfit water quality except in places like Banjara Hills, Erragadda and Tolichowki. Appropriate methods for improving the water quality in affected areas have been suggested

Continuous removal of Cr(VI) by lab-scale fixed-bed column packed with chitosan-nanomagnetite particles

Hexavalent Chromium species are classified as hazardous compounds due to their high toxic potential, considering also their remarkable solubility and redox potential. Various processes have been developed to remove/recover Cr(VI) species from polluted groundwater, such as membrane processes, ion-exchange and adsorption and chemical or biochemical reduction. Indeed, the reduction/removal process of Cr(VI) through iron-based materials usually leads to a pH increase of the reaction medium, allowing to facilitate the subsequent precipitation of the Cr(III) species. In this context, the use of iron based nano-particles (IBNs) supported on bio-polymer matrix allowed to maximize the Cr(VI) removal capacities of iron-based materials, leading to the production of high active and eco-compatible nano-materials. The use of chitosan as surface-modified agent, allows the reduction of aggregation forces among the produced IBNs, leading to higher surface active areas and chemical reactivity. At the same time, the use of a bio-polymer increases the eco-compatibility of the IBNs, reducing the possible interaction with bacteria and microorganisms during the treatment process. In this work chitosan-nanomagnetite particles were synthetized and employed as packing material inside fixed-bed lab-scale column (height 25 cm and diameter of 1.5 cm) to remove, in continuous, Cr(VI) species from synthetic wastewaters. The tests were performed at different inlet flow-rate values (2, 5 and 7 mL/min) at fixed Cr(VI) initial concentration (20 mg/L) and varying the solution pH (pH=4 and 7). The obtained breakthrough curves were then modeled according to the classical dynamic Thomas model