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  • Anwar, Waheed  (3)
  • 1
    Online Resource
    Online Resource
    Hindawi Limited ; 2020
    In:  Journal of Sensors Vol. 2020 ( 2020-10-24), p. 1-17
    In: Journal of Sensors, Hindawi Limited, Vol. 2020 ( 2020-10-24), p. 1-17
    Abstract: Getting quality sleep is important for every person to get better physical health. Irregular sleep patterns may indicate the illness resulting in chronic depression, which makes the evaluation of the sleep cycle mandatory for a healthy body and mind. In the arena of globalization, along with the increased facilities, various other challenges have been probed to provide the quality health care facilities with the use of economical instruments and technology. The development of the Internet of Things (IoT) technology purports the preambles to build a consistent and cost-effective system to monitor the sleep quality of patients. Several other systems are available for this purpose; however, such systems are very costly and difficult to implement. To overcome the issue, this study suggests an inventive system to monitor and analyze the sleep patterns using ambient parameters. The proposed system is effective enough that it can proficiently monitor patient’s sleep using Commercial off the Shelf (COS) sensors as well as predicts the results using the intelligent capability of the random forest model. The patient’s bio status including physical movement of the body, heartbeat, SPO2 level (oxygen saturation in the blood for the proper functioning of the body), and snoring patterns could be measured through this system, in which recorded data is transmitted to the computer system in a real-time environment. This system consists of two parts. One part consists of analyzing the behavior of data using the intelligent technique of the random forest model and decision rules in a real-time environment. This real-time analysis notifies the caretaker about the situation of the patient. In the second part, batch data processing is performed which allows the detailed analysis of data using statistical methods to produce the overall condition of the patient in a specified interval of time. Through the proposed system, we can easily measure the sleep patterns of patients and provide them with better treatment by using this simple and cost-effective system. The result of the conducted research shows that the proposed technique provides 95% accuracy. The patient’s sleep data is used to test this method through the validation of manual results, which provides the minimum error rate. This study highlights the implementation of an intelligent and smart sleep quality monitoring system using IoT on a variant number of people with minimum expense rate.
    Type of Medium: Online Resource
    ISSN: 1687-7268 , 1687-725X
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2020
    detail.hit.zdb_id: 2397931-8
    Location Call Number Limitation Availability
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  • 2
    In: Complexity, Hindawi Limited, Vol. 2021 ( 2021-2-27), p. 1-16
    Abstract: Smart parsimonious and economical ways of irrigation have build up to fulfill the sweet water requirements for the habitants of this world. In other words, water consumption should be frugal enough to save restricted sweet water resources. The major portion of water was wasted due to incompetent ways of irrigation. We utilized a smart approach professionally capable of using ontology to make 50% of the decision, and the other 50% of the decision relies on the sensor data values. The decision from the ontology and the sensor values collectively become the source of the final decision which is the result of a machine learning algorithm (KNN). Moreover, an edge server is introduced between the main IoT server and the GSM module. This method will not only avoid the overburden of the IoT server for data processing but also reduce the latency rate. This approach connects Internet of Things with a network of sensors to resourcefully trace all the data, analyze the data at the edge server, transfer only some particular data to the main IoT server to predict the watering requirements for a field of crops, and display the result by using an android application edge.
    Type of Medium: Online Resource
    ISSN: 1099-0526 , 1076-2787
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2021
    detail.hit.zdb_id: 2004607-8
    SSG: 11
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  • 3
    Online Resource
    Online Resource
    Hindawi Limited ; 2021
    In:  Scientific Programming Vol. 2021 ( 2021-7-10), p. 1-17
    In: Scientific Programming, Hindawi Limited, Vol. 2021 ( 2021-7-10), p. 1-17
    Abstract: Agriculture is suffering from the problem of low fertility and climate hazards such as increased pest attacks and diseases. Early prediction of pest attacks can be very helpful in improving productivity in agriculture. Insect pest (whitefly) attack has a high influence on cotton crop yield. Internet of Things solution is proposed to predict the whitefly attack to take prevention measures. An insect pest prediction system (IPPS) was developed with the help of the Internet of Things and a RBFN algorithm based on environmental parameters such as temperature, humidity, rainfall, and wind speed. Pest Warning and Quality Control of Pesticides proposed an economic threshold level for prediction of whitefly attack. The economic threshold level and RBFN algorithm are used to predict the whitefly attack using temperature, humidity, rainfall, and wind speed. The seven evaluation metrics accuracy, f-measures, precision, recall, Cohen’s kappa, ROC AUC, and confusion matrix are used to determine the performance of the RBFN algorithm. The proposed insect pest prediction system is deployed in the high influenced region of pest that provides pest prediction information to the farmer to take control measures.
    Type of Medium: Online Resource
    ISSN: 1875-919X , 1058-9244
    RVK:
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2021
    detail.hit.zdb_id: 2070004-0
    Location Call Number Limitation Availability
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