A method of measuring turbidity based on a multi-wavelength spectral sensor is proposed by using SFH4737 broad-band infrared LED,a multi-wavelength spectral sensor and independently developed data processing software....A method of measuring turbidity based on a multi-wavelength spectral sensor is proposed by using SFH4737 broad-band infrared LED,a multi-wavelength spectral sensor and independently developed data processing software.Combining multiple wavelength data from the sensor,the unitary and multivariate fitting models were constructed to investigate the relationship among light intensity information,absorbance and turbidity,respectively.The turbidity of the actual water bodies was measured separately by using proposed method and a commercially visible spectrophotometer.The independent-samples T test(p>0.05)showed that there was no significant difference between the method in this paper and the standard assay method.The method is simple and inexpensive,and can be applied to the rapid detection of water turbidity,providing a new way of industrial online measurement.展开更多
This research explored a novel multimodal approach for disease management in cauliflower crops.With the rising challenges in sustainable agriculture,the research focused on a patch spraying method to control disease a...This research explored a novel multimodal approach for disease management in cauliflower crops.With the rising challenges in sustainable agriculture,the research focused on a patch spraying method to control disease and reduce crop losses and environmental impact.For non-destructive disease assessment,a spectral sensor was used to collect spectral information from diseased and healthy cauliflower parts.The spectral data sets were analyzed using decision tree and support vector machine(SVM)algorithms to identify the most accurate model for distinguishing diseased and healthy plants.The chosen model was integrated with a low-volume sprayer(50-150 L·ha^(-1)),equipped with an electronic control unit for targeted spraying based on sensor-detected regions.The decision tree model achieved 89.9% testing accuracy,while the SVM model achieved 96.7% accuracy using hyperparameters:cost of 10.0 and tolerance of 0.001.The research successfully demonstrated the integration of spectral sensors,machine learning,and targeted spraying technology for precise input application.Additionally,the optimized sprayer achieved a 72.5% reduction in chemical usage and a significant time-saving of 21.0% compared to a standard sprayer for black rot-infested crops.These findings highlight the potential efficiency and resource conservation benefits of innovative sprayer technology in precision agriculture and disease management.展开更多
Infrared and visible light image fusion technology is a hot spot in the research of multi-sensor fusion technology in recent years. Existing infrared and visible light fusion technologies need to register before fusio...Infrared and visible light image fusion technology is a hot spot in the research of multi-sensor fusion technology in recent years. Existing infrared and visible light fusion technologies need to register before fusion because of using two cameras. However, the application effect of the registration technology has yet to be improved. Hence, a novel integrative multi-spectral sensor device is proposed for infrared and visible light fusion, and by using the beam splitter prism, the coaxial light incident from the same lens is projected to the infrared charge coupled device （CCD） and visible light CCD, respectively. In this paper, the imaging mechanism of the proposed sensor device is studied with the process of the signals acquisition and fusion. The simulation experiment, which involves the entire process of the optic system, signal acquisition, and signal fusion, is constructed based on imaging effect model. Additionally, the quality evaluation index is adopted to analyze the simulation result. The experimental results demonstrate that the proposed sensor device is effective and feasible.展开更多
A spectral reflectance sensor(SRS)fixed on the near-surface ground was developed to support the continuous monitoring of vegetation indices such as the normalized difference vegetation index(NDVI)and photochemical ref...A spectral reflectance sensor(SRS)fixed on the near-surface ground was developed to support the continuous monitoring of vegetation indices such as the normalized difference vegetation index(NDVI)and photochemical reflectance index(PRI).NDVI is useful for indicating crop growth/phenology,whereas PRI was developed for observing physiological conditions.Thus,the seasonal change patterns of NDVI and PRI are two valuable pieces of information in a crop-monitoring system.However,capturing the seasonal patterns is considered challenging because the vegetation index values estimated by the reflection from vegetation are often governed by meteorological conditions,such as solar irradiance and precipitation.Further,unlike growth/phenology,the physiological condition has diurnal changes as well as seasonal characteristics.This study proposed a novel filtering method for extracting the seasonal signals of SRS-based NDVI and PRI in paddy rice,barley,and garlic.First,the measurement accuracy of SRSs was compared with handheld spectrometers,and the R^(2)values between the two devices were 0.96 and 0.81 for NDVI and PRI,respectively.Second,the experimental study of threshold criteria with respect to meteorological variables(i.e.,insolation,cloudiness,sunshine duration,and precipitation)was conducted,and sunshine duration was the most useful one for excluding distorted values of the vegetation indices.After data processing based on sunshine duration,the R^(2)values between the measured vegetation indices and the extracted seasonal signals of vegetation indices increased by approximately 0.002–0.004(NDVI)and 0.065–0.298(PRI)on the three crops,and the seasonal signals of vegetation indices became noticeably improved.This method will contribute to an agricultural monitoring system by identifying the seasonal changes in crop growth and physiological conditions.展开更多
This research,by use of RS image_simulating method,simulated apparent reflectance images at sensor level and ground_reflectance images of SPOT_HRV,CBERS_CCD,Landsat_TM and NOAA14_AVHRR’s corresponding bands.These ima...This research,by use of RS image_simulating method,simulated apparent reflectance images at sensor level and ground_reflectance images of SPOT_HRV,CBERS_CCD,Landsat_TM and NOAA14_AVHRR’s corresponding bands.These images were used to analyze sensor’s differences caused by spectral sensitivity and atmospheric impacts.The differences were analyzed on Normalized Difference Vegetation Index(NDVI).The results showed that the differences of sensors’ spectral characteristics cause changes of their NDVI and reflectance.When multiple sensors’ data are applied to digital analysis,the error should be taken into account.Atmospheric effect makes NDVI smaller,and atmospheric correction has the tendency of increasing NDVI values.The reflectance and their NDVIs of different sensors can be used to analyze the differences among sensor’s features.The spectral analysis method based on RS simulated images can provide a new way to design the spectral characteristics of new sensors.展开更多
Wireless multimedia sensor network (WMSN) consists of sensors that can monitor multimedia data from its surrounding, such as capturing image, video and audio. To transmit multimedia information, large energy is requir...Wireless multimedia sensor network (WMSN) consists of sensors that can monitor multimedia data from its surrounding, such as capturing image, video and audio. To transmit multimedia information, large energy is required which decreases the lifetime of the network. In this paper we present a clustering approach based on spectral graph partitioning (SGP) for WMSN that increases the lifetime of the network. The efficient strategies for cluster head selection and rotation are also proposed.展开更多
A universal spectral modulation sensor with low cost,stable,reliable and accurate performances is presented.The optical measuring device using a universal spectral modulation sensor is immune to change the intensities...A universal spectral modulation sensor with low cost,stable,reliable and accurate performances is presented.The optical measuring device using a universal spectral modulation sensor is immune to change the intensities of the light source and light transmission due to optical fiber bending and optical fiber connector loss.The spectral modulation sensor system can detect and measure various physical parameters such as pressure,temperature,gas density,and various chemical species.展开更多
Wireless Multimedia Sensor Networks (WMSNs) are comprised of small embedded audio/video motes capable of extracting the surrounding environmental information, locally processing it and then wirelessly transmitting it ...Wireless Multimedia Sensor Networks (WMSNs) are comprised of small embedded audio/video motes capable of extracting the surrounding environmental information, locally processing it and then wirelessly transmitting it to sink/base station. Multimedia data such as image, audio and video is larger in volume than scalar data such as temperature, pressure and humidity. Thus to transmit multimedia information, more energy is required which reduces the lifetime of the network. Limitation of battery energy is a crucial problem in WMSN that needs to be addressed to prolong the lifetime of the network. In this paper we present a clustering approach based on Spectral Graph Partitioning (SGP) for WMSN that increases the lifetime of the network. The efficient strategies for cluster head selection and rotation are also proposed as part of clustering approach. Simulation results show that our strategy is better than existing strategies.展开更多
基金National Natural Science Foundation of China(No.71801108)Natural Science Fund for Colleges and Universities of Anhui Province(No.KJ2017ZD32)。
文摘A method of measuring turbidity based on a multi-wavelength spectral sensor is proposed by using SFH4737 broad-band infrared LED,a multi-wavelength spectral sensor and independently developed data processing software.Combining multiple wavelength data from the sensor,the unitary and multivariate fitting models were constructed to investigate the relationship among light intensity information,absorbance and turbidity,respectively.The turbidity of the actual water bodies was measured separately by using proposed method and a commercially visible spectrophotometer.The independent-samples T test(p>0.05)showed that there was no significant difference between the method in this paper and the standard assay method.The method is simple and inexpensive,and can be applied to the rapid detection of water turbidity,providing a new way of industrial online measurement.
基金supported by the Technology Development Programme of Department of Science and Technology,Government of India(DST/TDT/TDP-22/2022)。
文摘This research explored a novel multimodal approach for disease management in cauliflower crops.With the rising challenges in sustainable agriculture,the research focused on a patch spraying method to control disease and reduce crop losses and environmental impact.For non-destructive disease assessment,a spectral sensor was used to collect spectral information from diseased and healthy cauliflower parts.The spectral data sets were analyzed using decision tree and support vector machine(SVM)algorithms to identify the most accurate model for distinguishing diseased and healthy plants.The chosen model was integrated with a low-volume sprayer(50-150 L·ha^(-1)),equipped with an electronic control unit for targeted spraying based on sensor-detected regions.The decision tree model achieved 89.9% testing accuracy,while the SVM model achieved 96.7% accuracy using hyperparameters:cost of 10.0 and tolerance of 0.001.The research successfully demonstrated the integration of spectral sensors,machine learning,and targeted spraying technology for precise input application.Additionally,the optimized sprayer achieved a 72.5% reduction in chemical usage and a significant time-saving of 21.0% compared to a standard sprayer for black rot-infested crops.These findings highlight the potential efficiency and resource conservation benefits of innovative sprayer technology in precision agriculture and disease management.
基金This study is supported by the Natural Science Foundation of China （Grant No. 51274150） and Shanxi Province Natural Science Foundation of China （Grant No. 201601 D011059）.
文摘Infrared and visible light image fusion technology is a hot spot in the research of multi-sensor fusion technology in recent years. Existing infrared and visible light fusion technologies need to register before fusion because of using two cameras. However, the application effect of the registration technology has yet to be improved. Hence, a novel integrative multi-spectral sensor device is proposed for infrared and visible light fusion, and by using the beam splitter prism, the coaxial light incident from the same lens is projected to the infrared charge coupled device （CCD） and visible light CCD, respectively. In this paper, the imaging mechanism of the proposed sensor device is studied with the process of the signals acquisition and fusion. The simulation experiment, which involves the entire process of the optic system, signal acquisition, and signal fusion, is constructed based on imaging effect model. Additionally, the quality evaluation index is adopted to analyze the simulation result. The experimental results demonstrate that the proposed sensor device is effective and feasible.
基金supported by the Rural Development Administration(PJ013821032020),Republic of Korea。
文摘A spectral reflectance sensor(SRS)fixed on the near-surface ground was developed to support the continuous monitoring of vegetation indices such as the normalized difference vegetation index(NDVI)and photochemical reflectance index(PRI).NDVI is useful for indicating crop growth/phenology,whereas PRI was developed for observing physiological conditions.Thus,the seasonal change patterns of NDVI and PRI are two valuable pieces of information in a crop-monitoring system.However,capturing the seasonal patterns is considered challenging because the vegetation index values estimated by the reflection from vegetation are often governed by meteorological conditions,such as solar irradiance and precipitation.Further,unlike growth/phenology,the physiological condition has diurnal changes as well as seasonal characteristics.This study proposed a novel filtering method for extracting the seasonal signals of SRS-based NDVI and PRI in paddy rice,barley,and garlic.First,the measurement accuracy of SRSs was compared with handheld spectrometers,and the R^(2)values between the two devices were 0.96 and 0.81 for NDVI and PRI,respectively.Second,the experimental study of threshold criteria with respect to meteorological variables(i.e.,insolation,cloudiness,sunshine duration,and precipitation)was conducted,and sunshine duration was the most useful one for excluding distorted values of the vegetation indices.After data processing based on sunshine duration,the R^(2)values between the measured vegetation indices and the extracted seasonal signals of vegetation indices increased by approximately 0.002–0.004(NDVI)and 0.065–0.298(PRI)on the three crops,and the seasonal signals of vegetation indices became noticeably improved.This method will contribute to an agricultural monitoring system by identifying the seasonal changes in crop growth and physiological conditions.
文摘This research,by use of RS image_simulating method,simulated apparent reflectance images at sensor level and ground_reflectance images of SPOT_HRV,CBERS_CCD,Landsat_TM and NOAA14_AVHRR’s corresponding bands.These images were used to analyze sensor’s differences caused by spectral sensitivity and atmospheric impacts.The differences were analyzed on Normalized Difference Vegetation Index(NDVI).The results showed that the differences of sensors’ spectral characteristics cause changes of their NDVI and reflectance.When multiple sensors’ data are applied to digital analysis,the error should be taken into account.Atmospheric effect makes NDVI smaller,and atmospheric correction has the tendency of increasing NDVI values.The reflectance and their NDVIs of different sensors can be used to analyze the differences among sensor’s features.The spectral analysis method based on RS simulated images can provide a new way to design the spectral characteristics of new sensors.
文摘Wireless multimedia sensor network (WMSN) consists of sensors that can monitor multimedia data from its surrounding, such as capturing image, video and audio. To transmit multimedia information, large energy is required which decreases the lifetime of the network. In this paper we present a clustering approach based on spectral graph partitioning (SGP) for WMSN that increases the lifetime of the network. The efficient strategies for cluster head selection and rotation are also proposed.
文摘A universal spectral modulation sensor with low cost,stable,reliable and accurate performances is presented.The optical measuring device using a universal spectral modulation sensor is immune to change the intensities of the light source and light transmission due to optical fiber bending and optical fiber connector loss.The spectral modulation sensor system can detect and measure various physical parameters such as pressure,temperature,gas density,and various chemical species.
文摘Wireless Multimedia Sensor Networks (WMSNs) are comprised of small embedded audio/video motes capable of extracting the surrounding environmental information, locally processing it and then wirelessly transmitting it to sink/base station. Multimedia data such as image, audio and video is larger in volume than scalar data such as temperature, pressure and humidity. Thus to transmit multimedia information, more energy is required which reduces the lifetime of the network. Limitation of battery energy is a crucial problem in WMSN that needs to be addressed to prolong the lifetime of the network. In this paper we present a clustering approach based on Spectral Graph Partitioning (SGP) for WMSN that increases the lifetime of the network. The efficient strategies for cluster head selection and rotation are also proposed as part of clustering approach. Simulation results show that our strategy is better than existing strategies.
文摘为提升法布里-珀罗(Fabry-Pérot,F-P)传感器游标光谱信号解调的准确性,提出基于深度学习的光谱数据直接解调方法。首先对光谱数据进行预处理,将复杂的游标光谱信息转化为卷积神经网络(Convolutional Neural Network,CNN)可以处理的数据格式,然后采用深度学习模型对预处理后的完整光谱数据进行训练和测试,并利用卷积神经网络对光谱数据进行特征提取和分类,最终实现待测信号的准确解调。使用灵敏度为112.5 nm/MPa的双腔法布里-珀罗传感器采集光谱数据,并开展信号解调实验,结果表明:CNN模型对未知光谱进行10折(fold)交叉验证的平均准确率为92.49%,均方根误差RRMSE(Root Mean Square Error,RMSE)为0.0392 MPa,相对误差的平均值为3.31%;卷积神经网络-长短期记忆(Convolutional Neural Network-Long Short Term Memory,CNN-LSTM)模型对未知光谱进行10折交叉验证的平均准确率为96.98%,RRMSE为0.0390 MPa,相对误差的平均值为3.28%。基于CNN-LSTM模型的方法仅通过解调256个采样点的数据就实现了较高准确度,具有便捷、高效的优点,为推动光谱信号解调领域发展提供了有效的技术途径,为开发智能光学传感系统提供了重要参考。
