A Novel IOT-Based Medicine Consumption System for Elders

Abdullah, Raiyaan; Ahmed, Riad; Jamal, Lafifa

doi:10.1007/s42979-022-01367-8

Cited by 2 publications

(4 citation statements)

References 9 publications

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“…In Ref. [53], Abdullah et al presented an IoT device for recognizing medicine names to manage the medicine consumption of elderly people by using the OCR model and Bidirectional LSTM (BiLSTM) algorithm. Chang et al in [54] demonstrated the implementation of the OCR model in an intelligent medicine dispensing system to detect medicine bag information.…”

Section: Use Cases In Iot Applications and Characteristics Overviewmentioning

confidence: 99%

“…In Ref. [53], Abdullah et al demonstrated the integration of EasyOCR models with the BiLSTM algorithm to improve text recognition results. These integrations implement the adaptability of OCR models and the ability to benefit from complementary algorithms in specialized use cases.…”

Section: Use Cases In Iot Applications and Characteristics Overviewmentioning

confidence: 99%

“…The addition of hardware accelerations is one solution to meet this demand. While the algorithms can be adapted for deployments on edge devices, it is noteworthy that additional GPUs will be required to achieve better performances, as shown in the studies of Glasenapp et al in [50], Tham et al in [51], Abdullah et al in [53], Dilshad et al in [55] and Cao et al in [58].…”

Section: Use Cases In Iot Applications and Characteristics Overviewmentioning

confidence: 99%

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A Survey of AI Techniques in IoT Applications with Use Case Investigations in the Smart Environmental Monitoring and Analytics in Real-Time IoT Platform

Panduman,

Funabiki,

Fajrianti

et al. 2024

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In this paper, we have developed the SEMAR (Smart Environmental Monitoring and Analytics in Real-Time) IoT application server platform for fast deployments of IoT application systems. It provides various integration capabilities for the collection, display, and analysis of sensor data on a single platform. Recently, Artificial Intelligence (AI) has become very popular and widely used in various applications including IoT. To support this growth, the integration of AI into SEMAR is essential to enhance its capabilities after identifying the current trends of applicable AI technologies in IoT applications. In this paper, we first provide a comprehensive review of IoT applications using AI techniques in the literature. They cover predictive analytics, image classification, object detection, text spotting, auditory perception, Natural Language Processing (NLP), and collaborative AI. Next, we identify the characteristics of each technique by considering the key parameters, such as software requirements, input/output (I/O) data types, processing methods, and computations. Third, we design the integration of AI techniques into SEMAR based on the findings. Finally, we discuss use cases of SEMAR for IoT applications with AI techniques. The implementation of the proposed design in SEMAR and its use to IoT applications will be in future works.

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Section: Use Cases In Iot Applications and Characteristics Overviewmentioning

confidence: 99%

Section: Use Cases In Iot Applications and Characteristics Overviewmentioning

confidence: 99%

Section: Use Cases In Iot Applications and Characteristics Overviewmentioning

confidence: 99%

See 1 more Smart Citation

A Survey of AI Techniques in IoT Applications with Use Case Investigations in the Smart Environmental Monitoring and Analytics in Real-Time IoT Platform

Panduman,

Funabiki,

Fajrianti

et al. 2024

Information

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“…The system should be affordable and able to be manufactured at scale. As seen in the work [3], a home device can be very useful to elders. If we develop a home device to monitor and evaluate the exercise of elderly people, it will greatly benefit them.…”

Section: Introductionmentioning

confidence: 99%

STPT: Spatio-Temporal Polychromatic Trajectory Based Elderly Exercise Evaluation System

2023

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This paper introduces an elderly exercise evaluation system. To determine the quality of a performed exercise, the authors propose a novel system to generate and use Spatio-Temporal Polychromatic Trajectory (STPT) images. Usually, the elder people need to perform some exercises or take physiotherapy in order to stay healthy both physically and mentally. It becomes difficult to evaluate the quality of their exercise routine without the aid of a trained physiotherapist. The system aims to overcome this problem by allowing elders to record their exercise videos using an easy-to-use Graphical User Interface and evaluate the results. A dataset of 109 subjects performing four types of shoulder exercises several times was created. The videos are labelled as correct or incorrect and an STPT image is generated from each video. Using our newly introduced method, the movement of the elder person is projected into an image which can be input to a Convolutional Neural Network (CNN). The dataset is further augmented to increase accuracy. Using our proposed method, the best model achieved an F1 Score over 90% in three of the four exercises. The CNN is trained based on these clips and the models are added to the backend of the interface. The proposed system requires only an ordinary camera and a computer with an entry level GPU allowing it to be deployed at a large scale.

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A Novel IOT-Based Medicine Consumption System for Elders

Cited by 2 publications

References 9 publications

A Survey of AI Techniques in IoT Applications with Use Case Investigations in the Smart Environmental Monitoring and Analytics in Real-Time IoT Platform

A Survey of AI Techniques in IoT Applications with Use Case Investigations in the Smart Environmental Monitoring and Analytics in Real-Time IoT Platform

STPT: Spatio-Temporal Polychromatic Trajectory Based Elderly Exercise Evaluation System

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