Use Of Drones in an Underground Mine for Geotechnical Monitoring

Geotechnical monitoring is a significant aspect of mining. This includes traditional monitoring with extensometers and stress meters, as well as new technologies which include Lidar, Radar, advanced wireless sensors, and many other new technologies. Underground mining has unique and significant safety hazards compared to surface mining, due to high stress concentrations, weak rock masses, and limited access and air quality. Underground mining methods that utilize large open stopes is one example. After each production blast in open stopes, for example, the rock can become unstable due to excessive vibrations. Since not all the areas inside stopes are accessible, it can be unsafe to put costly production equipment like Load Haul Dump (LHD) vehicles and drilling jumbos inside the stopes. Secondary blasting also becomes hazardous as it requires mining personnel to enter hazardous areas. Traditional monitoring equipment for stope monitoring is ineffective and impractical in most cases, due to the difficulties in placing the monitoring equipment inside unsafe areas of the stopes. The use of a drone can improve safety compared to other surveying systems. In addition, underground monitoring utilizing drones delivers fast results, gives real-time results, and minimizes human exposure in unsafe underground conditions. The mining industry already is benefiting from the rapidly advancing drone technologies. However, most of the drone use now is for is for surface mining, and its use in underground mining is still an area that needs significant research and development. A drone stabilizes itself using GPS, but in certain places and locations, this is not always possible; for example, under a bridge, inside a building or in an underground mine. Also, it is not safe for human personnel to enter all locations in a mine because areas can be dangerous due to loose hanging rocks and unsafe air quality. The unavailability of GPS, the low light conditions, and the confined spaces make it very difficult and challenging to use drones in an underground space, and hence University research in this area is both important and necessary. The research described in this thesis includes the following four areas: 1. Purchasing a drone and demonstrating that it can be controlled and used to capture images in an underground environment with confined space. 2. Developing a solution for drones to work in the dark underground mine environment with the use of specially designed lights attached to the drone. 3. Optimizing the settings in the drone camera to capture images of significant quality and quantity to producing high-density three-dimensional point clouds. 4. Demonstrating that the point clouds produced from underground drone monitoring are enough to extract geotechnical rock mass characteristics and rock mass movement using point cloud processing programs

A Comparative Analysis of Retrievability and PageRank Measures

The accessibility of documents within a collection holds a pivotal role in Information Retrieval, signifying the ease of locating specific content in a collection of documents. This accessibility can be achieved via two distinct avenues. The first is through some retrieval model using a keyword or other feature-based search, and the other is where a document can be navigated using links associated with them, if available. Metrics such as PageRank, Hub, and Authority illuminate the pathways through which documents can be discovered within the network of content while the concept of Retrievability is used to quantify the ease with which a document can be found by a retrieval model. In this paper, we compare these two perspectives, PageRank and retrievability, as they quantify the importance and discoverability of content in a corpus. Through empirical experimentation on benchmark datasets, we demonstrate a subtle similarity between retrievability and PageRank particularly distinguishable for larger datasets.Comment: Accepted at FIRE 202

Growth dynamics of deciduous species during their life period: A case study of urban green space in India

It is evident that grass density (GD) and shoot growth rate (SGR) governs the differential settlement of substructure, groundwater recharge, and stability of green infrastructure. GD and SGR are usually assumed to be constant during the entire life period of vegetation. However, spatial and temporal dynamics of GD and SGR in urban green space were rarely explored previously. The main objective of this study is to explore the spatial and temporal dynamics of GD and SGR in urban space vegetated with deciduous species (mix grass i.e., Poaceae and Bauhinia purpurea). Field monitoring was conducted in the urban green space for one year (i.e., life period of selected species). The monitoring period includes the growth period and gradual wilting period. Substantial spatial variation of GD was found during the first six months. GD away from the tree trunk was found to be 1.02–56.3 times higher than that near the tree trunk during the first six months. Thereafter, any spatial variation of GD was not found in the next six months. Unlike the GD, SGR was found to vary during the entire life period of mix grass. In addition, SGR away from the tree trunk was found to be 1.1–4.6 times higher than that near the tree trunk. Any relationship between GD and rainfall depth was not found. Whereas, SGR mainly depends on rainfall depth. The hypothesis of uniformity in GD and SGR during the life period of deciduous species was not found to be true

IoT Based Smart Electricity Energy Meter using ESP32 and Blynk Application

<p><i>The growing global concern for efficient energy consumption and environmental sustainability has spurred the development of innovative technologies to monitor and manage energy usage. In this context, this project presents the design and implementation of a smart energy meter using the Blynk application  as an IoT interface. The integration of Blynk offers a user-friendly and accessible platform for real-time energy monitoring, data visualization, and remote control, enabling individuals and organizations to make informed decisions about their energy consumption patterns. The smart energy meter system consists of an energy meter, a microcontroller, and connectivity modules. The energy meter serves as the primary data source, measuring electricity consumption and providing key parameters such as voltage, current, and power factor. The microcontroller, based on Arduino, acts as the central processing unit, collecting data from the energy meter and establishing a connection with the Blynk application through Wi-Fi or Ethernet connectivity modules. This connection enables seamless data transmission and synchronization with the Blynk server, facilitating real-time energy monitoring and control. The Blynk application serves as the user interface for energy data visualization and management. Users can access their energy consumption information through a smartphone or tablet, making it convenient and accessible from anywhere. The application's intuitive dashboard provides interactive charts, graphs, and statistics that enable users to monitor their energy usage patterns and identify potential inefficiencies. Additionally, the Blynk application offers features such as setting energy consumption thresholds and receiving notifications when limits are exceeded, empowering users to take proactive steps towards energy conservation. Remote control capabilities are another crucial aspect of the smart energy meter system. Through the Blynk application, users can remotely control connected devices or appliances, enabling them to schedule operations, turn off energy-consuming devices, or activate energy-saving modes. This functionality promotes energy conservation and facilitates the implementation of demand-response strategies in residential, commercial, and industrial settings. The project's significance lies in its potential to revolutionize energy monitoring and management practices. By leveraging the power of IoT technology and the user-friendly Blynk interface, the smart energy meter system provides an accessible and efficient solution for individuals and organizations to optimize their energy usage. It empowers users to make informed decisions based on real-time data, reducing energy waste, and promoting sustainable practices.</i></p&gt