J. Mobile Multimedia最新文献

{"title":"Tomato: Different Leaf Disease Detection Using Transfer Learning Based Network","authors":"Siva Prasad Patnayakuni","doi":"10.13052/jmm1550-4646.18313","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.18313","url":null,"abstract":"Plant diseases have a significant effect on crop productivity, financial costs, and output. It is vital to research plant diseases in order to increase agricultural yield. Tomatoes are the world’s most frequently cultivated crop, and they are a staple ingredient in almost every cuisine. After potatoes and sweet potatoes, tomato is the most extensively cultivated vegetable on the planet. India was ranked second in tomato output. Numerous diseases have a detrimental effect on the quantity and quality of the tomato crop. Early disease detection will assist farmers in increasing crop production. The research proposes a transfer learning-based technique for detecting five distinct leaf diseases. AlexNet has been used to detect and classify disease. The simulation results reveal that the method based on transfer learning outperforms the other methods with a classification accuracy of 95.6%.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116671505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Crop Recommendation and Yield Estimation Using Machine Learning","authors":"A. Ashwitha, C. Latha","doi":"10.13052/jmm1550-4646.18320","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.18320","url":null,"abstract":"In most developing countries like India, Agriculture is seen as one of the most widely followed habitations and contributes majorly to the country’s economy. Agriculture provides the primary source of food, income, livelihood and employment to the majority of rural populations in India. Many crops are destroyed every year due to a lack of technical knowledge and unpredictable weather patterns such as temperature, rainfall, and other atmospheric parameters, which play a massive role in deciding the crop yield and profit. Therefore, choosing the right crop to grow and enhancing crop yield is an essential aspect of improving real-life farming scenarios. One of the motives is to collect and integrate the agricultural data from specific regions that may be used to analyse the optimal crop and estimate the crop yield. This script is novel by using simple crop, soil and weather parameters like crop, the area under cultivation, nitrogen, phosphorus and potassium content of the soil, season, average rainfall and temperature of a district in Karnataka, India. The user can predict the most suitable crop and its estimated yield for a chosen year. This model uses primary classification, techniques like the random forest, k-NN, logistic regression, decision tree, XGBoost, SVM and gradient boosting classifier for determining the most suitable crop and regression algorithms like Linear Regression, k-NN, DBSCAN, Random Forest and ANN algorithm to estimate the yield of the most optimal crop identified earlier. The algorithm that has the least mean error is chosen for prediction and estimation and thus gives better results than the particular machine learning algorithm domain. There is a web interface for ease of use for end-users. Therefore, this project assists the farmers in choosing the suitable crop that can be grown in a particular region during a specific season or specific period and estimate its yield and predict if the recommended crop is profitable. Hence this project helps the farmers in preserving their time by assisting them in the decision-making process.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128162694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ASIS Edge Computing Model to Determine the Communication Protocols for IoT Based Irrigation","authors":"S. Premkumar, A. Sigappi","doi":"10.13052/jmm1550-4646.18321","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.18321","url":null,"abstract":"Internet of Things (IoT) provide a promising Smart irrigation facilitator for continual monitoring and control of environmental parameters, thereby leading to a huge volume of data to be efficiently collected, transferred, processed and stored. The deployment of cloud-based infrastructure with on-field connectedness, allowing information exchange among IoT nodes, and the usage of energy scavenging (e.g., solar power) in feeding them, become necessary, since agricultural fields are in lack of wired energy supply and, often, a reliable (Internet) network coverage. Therefore, these issues can be addressed through the integration of Edge computing in IoT scenarios. An efficient strategy is required to select the best communication technology with a motive of increasing the network performance between the IoT devices, Edge device and cloud. Application Specific Infrastructure Selection (ASIS) is an edge computing model developed to select the appropriate communication protocols according to the infrastructure requirements of three different real time scenarios namely: Assembly line automation, Smart parking system and Automatic irrigation system are deployed to get the most suitable application specific protocol from ZigBee, LoRa (Long Range) and LoWPAN (Low-Power Wireless Personal Area Network) to implement in real-time basis. ASIS model is proposed as a network resource manager that is capable of sensing, acting, signal processing, and/or communication abilities to perform a protocol selection according to their physical and technological limitations. Further Edge based ASIS model is developed to enhance the network performance even better when compared with cloud-based model. Automatic irrigation system is extended in the Edge based ASIS model. The overall ASIS system is evaluated by means of network parameters such as network usage, network delay and power consumption. The ASIS model and Edge based ASIS model is deployed in iFogSim simulator that compares each protocol used in the above IoT scenarios. Finally, the scenario of Automatic irrigation system is modeled using Edge based ASIS model where ZigBee with edge performs better compared with cloud-based model. Experimental results show that ASIS based Edge implementation lessen the overall network parameters in contrast to non-edge deployment in automatic irrigation scenario.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129159125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thyroid Disease Prediction Using XGBoost Algorithms","authors":"Sankar Sennan, Anupama Potti, G. Chandrika, S. Ramasubbareddy","doi":"10.13052/jmm1550-4646.18322","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.18322","url":null,"abstract":"Nowadays, thyroid disease is increasing rapidly all over the world. Significantly, one out of ten people is affected by the thyroid in India. In recent years, many researchers have done various research works on thyroid disease detection. Therefore, the early stage of thyroid disease prediction is difficult to protect and avoid the worst health condition. In this regard, the machine learning plays a crucial role to detect the disease accurately. We consider the UC Irvin knowledge discovery dataset. So, this paper proposes the XGBoost algorithm to predict thyroid disease accurately. The best features are selected using XGBoost function. The proposed XGBoost algorithm’s efficacy is compared to decision tree, logistic regression, k-Nearest Neighbor (kNN) methods. The performance of all four algorithms is compared and analyzed. It is observed that the accuracy of the XGBoost algorithm increases by 2% than the KNN algorithm.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128085794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DTTV Localization with Fingerprinting Technique and Clean Algorithm Based on Measurement Data","authors":"S. Promwong, Nattapan Suwansukho","doi":"10.13052/jmm1550-4646.18318","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.18318","url":null,"abstract":"Digital terrestrial television (DTTV) technology has been developed and used to broadcast the television program. A numerous applications have been developed for the additional feature used with DTTV. One of these features that can be used which is the localization system with DTTV broadcasting. The advantage of DVB-T2 broadcasting channel for localization technology which very wide coverage area that covered whether outdoor and indoor environment. In the present there are divers methodologies to locate the position of an object or user such as the Global Positioning System (GPS), Cellular Positioning System (CPS) and Wi-Fi Positioning System (WPS). Nowadays there are various application that used for monitoring and controlling such as a water level sensor system, a traffic control system, an intrusion monitoring system etc. that consists of the localization system. The received data can’t be useful without the accuracy location. The mentioned foregoing system still have a limitation in some environment such as the GPS signal is not accessible to some environments, the CPS signal is based on a cell phone tower and the WPS is based on Wi-Fi hotspot. Therefore, the accuracy of localization is decreased. In order to overcome the foregoing limitation of these three systems the complementary remedy the poor coverage is required. The objective of this research is to improve the DVB-T2 propagation channel by a Clean algorithm to eliminate the noise propagation channel for an accuracy of localization system. This technique is very useful for localization analysis in DTTV technology. The distinctive advantage of the DTTV localization is the wide coverage of signal whether an indoor or outdoor environment. Moreover, when the Clean algorithm has been used the noise in propagation channel has been eliminated lead to the accuracy of location receive.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130910049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Futuristic IoT based Smart Precision Agriculture: Brief Analysis","authors":"Iwin Thanakumar Joseph Swamidason, Shanthini Pandiyarajan, Karunakaran Velswamy, P. Jancy","doi":"10.13052/jmm1550-4646.18323","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.18323","url":null,"abstract":"Agriculture is considered as the backbone of any nation across the globe. With the advent of modern technologies, smart tools and techniques are used in the agriculture/farming to build on the quantity as well as quality of the agriculture production to feed the basic necessity of the humans. Smart technology such as Internet of Things play a vital role in monitoring and analyzing various environmental parameters such as water level, humidity, soil moisture, air quality, UV level, rain etc. which are highly essential to ensure the fruitful yield of any nutritious crops. In this research article, precision agriculture concepts are investigated widely with the focus of improving the productivity level and also the effective utilization of resources with the minimal cost while compared with the conventional methodologies.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125335571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of Brinjal Plant Disease Using Support Vector Machine and Convolutional Neural Network Algorithm Based on Deep Learning","authors":"Venkataramana Attada, K. Kumar, N. Suganthi, R. Rajeswari","doi":"10.13052/jmm1550-4646.18315","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.18315","url":null,"abstract":"Plant pathogens prediction is the prerequisite for timely and productive control of plant pathogens within complicated environments. However, the white mold is a complicated disease in a brinjal plant. Hence, to vanquish these difficulties a novel Deep Learning Integration (DLI) Techniques has been proposed. In Proposed system, classification is carried out by Support Vector Machine (SVM) and prediction is carried out by Convolutional Neural Network (CNN) Algorithm to predict the plant illness in Brinjal with high accuracy of 99.4%.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123198391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MSI-RPi: Affordable, Portable, and Modular Multispectral Imaging Prototype Suited to Operate in UV, Visible and Mid-Infrared Regions","authors":"Ajay Arunachalam, Henrik Andreasson","doi":"10.13052/jmm1550-4646.18312","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.18312","url":null,"abstract":"Digital plant inventory provides critical growth insights, given the associated data quality is good. Stable & high-quality image acquisition is critical for further examination. In this work, we showcase an affordable, portable, and modular spectral camera prototype, designed with open hardware’s and open-source software’s. The image sensors used were color, and infrared Pi micro-camera. The designed prototype presents the advantage as being low-cost and modular with respect to other general commercial market available spectral devices. The micro-size connected sensors make it a compact instrument that can be used for any general spectral acquisition purposes, along with the provision of custom selection of the bands, making the presented prototype design a Plug-nd-Play (PnP) setup that can be used in different wide application areas. The images acquired from our custom-built prototype were back-tested by performing image analysis and qualitative assessments. The image acquisition software, and processing algorithm has been programmed, which is bundled with our developed system. Further, an end-to-end automation script is integrated for the users to readily leverage the services on-demand. The design files, schematics, and all the related materials of the spectral block design is open-sourced with open-hardware license & is made available at https://github.com/ajayarunachalam/Multi-Spectral-Imaging-RaspberryPi-Design. The automated data acquisition scripts & the spectral image analysis done is made available at https://github.com/ajayarunachalam/SI-RPi.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128302226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental Evaluation of UWB Transmission Waveform with Body-Shadowing in an Indoor Environment","authors":"S. Suwan, S. Promwong","doi":"10.13052/jmm1550-4646.18319","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.18319","url":null,"abstract":"Wireless radio transmission performance in a realistic environment is a significant issue for designing and evaluating in short-range transmission technologies. Human body-shadowing is a significant propagation effect in an indoor wireless communication network. This paper presents the measurement model of impulse radio transmission with human body-shadowing in an indoor environment with IEEE 802.15.4 multipath impulse parameters. The impulse radio transfer function measurement model for the human body impulse radio transfer function with frequency band cover from 3 GHz to 11 GHz. The optimum system evaluation of impulse radio transmission is due to the human body and antennas. The characteristics of impulse radio transmission loss are using decay factor, log-normal standard, clusters, and ray arrival rate. The contributions of this research can be evaluating the human body impulse radio transfer function. And the design of the wireless radio system with the body shadowing effects and ambient environments.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129391101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3D Multimedia Packaging Design Based on Agile Software Development and IoT Platform","authors":"Patinya Sang-aroon, S. Prongnuch, S. Sitjongsataporn","doi":"10.13052/jmm1550-4646.1831","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1831","url":null,"abstract":"This paper aims to present the three-dimensional (3D) packaging structure design based on the agile software development and internet of things (IoT) platform, which an efficiency validation of IoT platform is required. The objective of this research is to investigate the model development of 3D multimedia-based packaging structure using the webserver design and agile software development applied in the design and implementation process. This model development methodology comprises how the IoT platform as the client-server architecture that is used to develop and support the orthographic projection techniques, information sheet, worksheet and multimedia presentation in the modern product design. The empirical results show the creative thinking of the group of young designers that can be achieved efficiently. The proposed model development can increase significantly the fundamental knowledge and interactive design ideas of young designers combining from the two-dimension to three-dimension packaging structure model.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133855411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}