IOT-Based Gemstone Detection and Analysis System

“A gemstone is a mineral stone that be formed from the result of geological processes and has a hardness above 7 Mohs” [2]. [1] This current research is undertaken to create a system that can identify the gemstones of the Corundum Family. According to [2], there are four characteristics that can be used to identify the type of gemstone based on physical aspects. These four aspects are refraction of light, the color, density, and hardness of the mineral contained in the stone. One of the countries that produce the most gemstones and has the highest proportion of gemstones is Sri Lanka. There are 200 diverse types of gemstones around the globe, but only about 75 distinct kinds of coloured and colourless gemstones from 10 primary families could be discovered in Sri Lanka. Although Sri Lanka is naturally rich in the gemstone industry, the methods or techniques that are used to verify and validate gemstones are yet manual and traditional. The gemstone trade continues to thrive as miners and traders are far more knowledgeable about the different varieties of gemstone families. The method of verifying gemstones is fraught with challenges for both clients and traders.  This research is conducted to invent an Internet of Things (IoT) based gemstone detector that can identify gemstones based on their refractive index, colour, and Cut-Shape, it is possible to effectively address the issues that customers and traders both confront. The refractive index, colour, and Cut-Shape of the gemstone will be determined via image processing, and the IoT device will be utilized to cluster the other elements

The contribution of amber to heritage tourism development

This article explores the relationship between amber and heritage tourism, utilizing Poland as an illustrative context. Amber, a form of fossilized resin, holds significant importance across a multitude of fields, such as science, culture, and economy, having been used as a material by artists, craftsmen, and jewelers for centuries. Today, amber draws visitors to locations where it is found and to institutions that display amber collections, such as museums and galleries. Furthermore, it is an essential component of various events, including exhibitions, fairs, and amber fishing competitions. Amber also forms the foundation of many tourist routes, such as the renowned Amber Route. Owing to its deep ties with cultural heritage, amber is considered a central attraction within amber-based heritage tourism. This paper examines the current contribution of amber to the development of heritage tourism. The authors conducted a literature analysis, online source queries, evaluations of institutions (e.g., museums), and personal observations to address the topic. The article is divided into eight sections, each highlighting different aspects of the investigated subject, ultimately suggesting an adaptation of Timothy and Boyd’s (2003) model to illustrate the development of amber-based heritage tourism

Researching of the deep neural network for amber gemstone classification

This project is based on the researching of the deep neural network for the classification of amber gemstone seen as a great opportunity to expand the range of application of the well known deep learning, which have been used more and more in different fields. First, it is explained the theoretical concepts about machine learning and deep learning, besides a little comparison between them in order to for the reader to make the thesis more understandable. It is also introduced the different machine learning classifiers and the different methods of deep learning which have been used during the presented work. After having the basic concepts it will be explained the different methods that have been studied throughout the thesis to find the best possible accuracy in the training, validation and testing of the data set. Finally, it will be showcased the different results obtained followed by a short explanation per each of them. In this work the main technique that will be used for the researching is the method of transfer learning. Due to the lack of huge amounts of database regarding the amber stones, this technique can be a lot profitable to achieve the best accuracy. Nevertheless other methods like training from scratch will be tested; in which it will be used YOLO (You Only Looks Once). There is plenty of developed architectures that can be used for transfer learning, but only AlexNet will be used, since is one of the most used. The main tool for performing all the training and testing is MATLAB, which is quite suitable for processing images and with the latest version now it is able to run deep neural network with ease.Outgoin