No abstract

Bengali is the seventh most spoken language, and 300 million people around the world speak in Bengali. The smart home is responsible for the digitization of modern society. This research reflects an Internet of Things (IoT) based smart solution, especially for the people who have a visual impairment along with the smart home. The proposed methodology presents a developed android application which will act as a smart assistant. The smart assistant is responsible for communicating with a blind person, browsing thoughts, and sharing ideas using the Bengali language. The proposed solution also focuses on the embodiment of IoT based blind stick. This article further assures a structural foundation of a smart home where blind persons and regular users will be able to control all the home appliances using Bengali voice command. This paper also illustrates experimental data analysis, such as transmission time calculation for GSM/GPRS and Bluetooth module, empirical coverage area calculation, a system usability scale (SUS), and data analysis of blind stick. We have found a SUS score of 84%. However, the proposed system will be beneficial and handy.

On the edge of the worldwide public health crisis, the COVID-19 disease has become a serious headache for its destructive nature on humanity worldwide. Wearing a facial mask can be an effective possible solution to mitigate the spreading of the virus and reduce the death rate. Thus, wearing a face mask in public places such as shopping malls, hotels, restaurants, homes, and offices needs to be enforced. This research work comes up with a solution of mask surveillance system utilizing the mechanism of modern computations like Deep Learning (DL), Internet of things (IoT), and Blockchain. The absence or displacement of the mask will be identified with a raspberry pi, a camera module, and the operations of DL and Machine Learning (ML). The detected information will be sent to the cloud server with the mechanism of IoT for real-time data monitoring. The proposed model also includes a Blockchain-based architecture to secure the transactions of mask detection and create efficient data security, monitoring, and storage from intruders. This research further includes an IoT-based mask detection scheme with signal bulbs, alarms, and notifications in the smartphone. To find the efficacy of the proposed method, a set of experiments has been enumerated and interpreted. This research work finds the highest accuracy of 99.95% in the detection and classification of facial masks. Some related experiments with IoT and Block-chain-based integration have also been performed and calculated the corresponding experimental data accordingly. A System Usability Scale (SUS) has been accomplished to check the satisfaction level of use and found the SUS score of 77%. Further, a comparison among existing solutions on three emergent technologies is included to track the significance of the proposed scheme. However, the proposed system can be an efficient mask surveillance system for COVID-19 and workable in real-time mask detection and classification.

No abstract

No abstract