No abstract

Nowadays, Dynamic industries like tourism is a enhance to boost many countries economy in recent years. The hotel sector leads to a significant role among all aspects of the tourism industry. Online travel platforms, in association with hotel management, are a part of hotel E-tourism that helps users to make travel plans online, suggest precise recommendations in consideration with the earlier feedbacks upon hotel stay. From the past few months, the user roaming ratio falls rapidly due to the COVID-19 Pandemic across the globe. In a business concern, this Pandemic affects all tourism sectors, specifically in the hotels’ occupancy. To retain business positions and attract the users in these problematic scenarios, hotel and travel platform management concerns about past preferences of users, which have a significant impact on gratification for a comfortable stay. The current market trends show that user reviews are playing a vital role to select a hotel based on a safe location. Our work tries to find and recommend the dimensions that contribute more towards higher satisfaction levels of users in Asian continental top tourism city hotels listed by the Master and VISA Inc survey with item collaborative filtering and regression techniques based on Tripadvisor reviews from social media in recent times. The outcome of the work is helpful for Asian continental hotel management to concentrate more on the dimensions for obtaining better reviews. From an online travel platform perspective, this work suggests the contexts for the travel recommender system to gain things effectively from users.

Nowadays Internet of Things (IoT) is the trending topic where we go. IoT is included in almost every device surrounded by us where valuable information is shared over the network to store it in the cloud or to transfer as a message alert to an individual. IoT devices generate a huge amount of data but only caring information is required and for that analytics needs to be performed. Analytics are reaching outside of the traditional datacenter towards the edge, where the IoT data is generated. So, here in this paper, the importance of secure data sharing over a network, generated by IoT devices is described and along with that the data flow between IoT and edge server is discussed, and the requirement of edge analytics is focused.

One of the most prevalent diseases that can be initially identified by visual inspection and further identified with the use of dermoscopic examination and other testing is skin cancer. Since eye observation provides the earliest opportunity for artificial intelligence to intercept various skin images, some skin lesion classification algorithms based on deep learning and annotated skin photos display improved outcomes. The researcher used a variety of strategies and methods to identify and stop diseases earlier. All of them yield positive results for identifying and categorizing diseases, but proper disease categorization is still lacking. Computer-aided diagnosis is one of the most crucial methods for more accurate disease detection, although it is rarely used in dermatology. For Feature Extraction, we introduced Spectral Centroid Magnitude (SCM). The given dataset is classified using an enhanced convolutional neural network; the first stage of preprocessing uses a median filter, and the final stage compares the accuracy results to the current method.

Fog computing is used for reducing the complexity level of a network architecture and processes the data in a fog node IoT Hub. The Internet of Things (IoT) will connect billions of devices, such as smart objects, which are heterogeneous in terms of hardware software and communication interfaces. The IoT has to this point grown as numerous vertical idea of the IoT, rather than focusing at the real creation of a highly interoperable infrastructure for the development of applications. For managing the various devices present in the hub we create an IP-based infrastructure so that the elements can be able to balance the diversified devices and the network elements are used to enhance the direct end to end communication which is much required. With all the above considerations we propose a Fog node i.e. an IoT hub that can be placed at the end of multiple networks thereby increasing the capability by implementing various functions such as allocation of resources border routers cache proxy servers etc. As the implementation of fog node is through the IoT hub here we would like to automate the resource allocation that takes place in the IoT hub