In this article, energy efficient ensemble clustering method (EECM) with black widow optimization (EECM-BWO) algorithm is proposed for effective data transmission with the help of real time flood disaster monitoring wireless sensor network (WSN). Initially, unified scalable ensemble clustering algorithm based on ensemble generation and consensus function is proposed for selecting the optimal routing path among the node using BWO algorithm. Then, biologically inspired routing black widow spiders optimization algorithm is proposed to trade off the nodes energy level, self-organization, and self-configuration in the WSN. The simulation is performed using NS2 simulator for validating the performance of the proposed EECM-BWO method. Here, in node, low delay achieves 24.07%, 72.58%, 51.36%, 81.75%, 77.74%, high packet delivery ratio achieves 70.83%, 53.93%, 90.23%, 43.58%, 24.58%, low packet drop attains 77.93%, 72.76%, 61.56%, 51.87%, 34.35%, low energy consumption attains 75.9%, 52.94%, 65.81%, 58%, 41.2% compared with existing energy-efficient clustering approach consolidated game theory as well as dual-cluster-head mode for WSNs energy-aware clustering by cuckoo optimization approach (EECM-COA), energy-aware clustering-based routing using multi-path reliable transmission with routing and control board (EECM-RCB-MRT), adaptive repair algorithm with temporally ordered routing algorithms for flood control strategy (EECM-AR-TORA-FCS), passive multi-hop clustering algorithm (EECM-PMC), dynamic source routing protocol based on genetic algorithm-bacterial foraging optimization (DSR-GA-BFO). 相似文献
In many wireless sensor network (WSN) applications, the location of a sensor node is crucial for determining where the event or situation of interest occurred. Therefore, localization is one of the critical challenges in WSNs. Mobile anchor node assisted localization (MANAL) is one of the promising solutions for the localization of statically deployed sensors. The main problem in MANAL localization is that the path planning of the mobile anchor (MA) node should be done so that the localization error in the network will be minimal and that all unknown nodes in the network are covered. This paper proposes a new path planning approach called nested hexagons curves (NHexCurves) for MANAL. NHexCurves guarantees that it will receive messages from at least three non-collinear anchors to locate all unknown nodes in the network. The proposed model has compared six different path planning schemes in the literature using weighted centroid localization (WCL). In these comparisons, first of all, localization errors of the models are compared using some statistical concepts. Second, the variation of the localization error according to parameters such as resolution (R) and the standard deviation of noise (σ) is observed. Then, with similar approaches, the standard deviation of errors, localization ratio, scalability performances, and finally, path lengths of the models are examined. The simulation results show that the NHexCurves static path planning model proposed in this study stands out compared to other models with high localization error and localization ratio performance, especially at low resolutions, due to its path design. At the same time, the lowest error values according to σ are obtained with the proposed model among all models considered. 相似文献
In an era of globalized trade relations where food and pharmaceutical products cross borders effortlessly, consumers face counterfeit and deteriorated products at elevated rates. This paper presents multifunctional, biodegradable hydrogel microparticles that can provide information on the authenticity and the potential deterioration of the tagged food or pharmaceutical formulations. These microparticles integrate spatially patterned authenticity code with two sensors—the first one detects possible presence of pathogenic microbes through monitoring pH while the second one identifies products stored above optimal temperatures via optical monitoring of the microparticle degradation. Particles are synthesized from a biocompatible polymer and a photoinitiator, dextran modified with 2‐hydroxyethylmethacrylate and riboflavin, respectively, using a continuous, high throughput method stop‐flow lithography. The proposed synthesis approach also enables crosslinking with visible light bringing about additional flexibility to flow lithography. Model liquid and solid food and pharmaceutical products are successfully labeled with microparticles and the functionality of the sensors in aqueous solutions is demonstrated. 相似文献
A gold immunochromatographic sensor (GICS) was developed for the rapid detection of 26 sulfonamides in honey samples.The sensor was based on a group-specific monoclonal antibody (mAb) that can recognize all 26 sulfonamides.Three haptens (hapten 1 with a thiazole ring,hapten 2 with a benzene ring,and hapten 3 with a straight carbon chain) were used for antigen preparation.With hybridoma technology,a group-specific mAb was screened with a 50% maximal inhibitory concentration (IC50) against sulfathizole (STZ) and the other 25 analogues ranging from 0.08 to 90.18 ng/mL.Mono-dispersed gold nanoparticles were conjugated with the mAb to develop the lateral immunochromatographic strip.A labeled antibody concentration of 0.1 μg/mL and a coating antigen concentration of 0.2 μg/mL in the test line were chosen for strip preparation.Under optimized conditions,the visual limits of detection (vLOD) for the concentrations of STZ,sulfamethoxazole,sulfamethizole,sulfadiazine,sulfamerazine,sulfadimethoxine,sulfamonomethoxine,sulfameter,sulfamethoxypyridazine,and sulfachloropyridazine were 5,0.25,0.25,10,5,10,25,2.5,5,0.25,and 10 μg/kg,respectively.Scanner analysis in honey samples revealed good performance for detection of the 26 sulfonamides.Commercial honey samples were tested with the sensor and positive results were confirmed with high-performance liquid chromatography.The proposed strip sensor provides a convenient method for the rapid and reliable determination of sulfonamides pollutants in honey samples. 相似文献
For rapid and simultaneous detection of (fluoro)quinolones, a broadly specific monoclonal antibody (mAb) that recognizes 32 (fluoro)quinolone antibiotics was prepared using a mixture of a norfloxacin derivative and a sarfloxacin derivative as the hapten. An immunochromatographic strip based on gold nanoparticles (AuNPs) was then assembled with goat anti-mouse antibody and antigen (sarfloxacin coupled to ovalbumin), used to form the C line and T line, respectively. This antigen competes with the (fluoro)quinolones in a sample incubated with mAbs labeled with AuNPs. The strip can detect 32 (fluoro)quinolones including oxolinic acid, nalidixic acid, miloxacin, pipemidic acid, piromidic acid, rosoxacin, cinoxacin, norfloxacin, pefloxacin, lomfloxacin, enofloxacin, fleroxacin, ciprofloxacin, enrofloxacin, dafloxacin, orbifloxacin, sparfloxacin, gemifloxacin, besifloxacin, balofloxacin, gatifloxacin, moxifloxacin, nadifloxacin, ofloxacin, marbofloxacin, flumequine, pazufloxacin, prulifloxacin, sarafloxacin, difloxacin, trovafloxacin, and tosufloxacin in milk within 10 min with the naked eye. The cut-off values of the strip range from 1 to 100 ng/mL and the limits of detection are 0.1–10 ng/mL. The strip does not cross-react with antibiotics including tetracycline, sulfamethazine, ampicillin, erythromycin, aflatoxin B1, or gentamicin. In short, this immunochromatographic strip is a very useful tool for the primary screening of (fluoro)quinolones in milk.