Software for precisely locating the location of objects

summary

I present my project - software for precisely locating the location of objects, which I developed as part of my engineering work. I conducted research in both ideal and real conditions, using three computational methods: trilateration, LBP (linear back projection) and ILBP (iterative linear back projection). I wrote the software in node.js as a server application supporting HTTP requests in accordance with REST principles.

Basics of the calculation method used

  1. Trilateration method
    • It uses distance measurement from at least three points to determine the location of an object.
    • Commonly used in geodesy, navigation, cartography and location in GPS systems and wireless networks.
    • The implementation is based on an algorithm available under the MIT license [38].
  2. LBP linear back projection method
    • A popular method of reconstructing images from projection data.
    • Used in object location systems, enabling accurate reconstruction of three-dimensional images.
    • Used, for example, in medicine in computed tomography
    • Implementation using our own algorithm written in C++.
  3. ILBP iterative linear feedback projection method
    • An improved version of LBP, enabling more accurate image reconstruction from projection data.
    • Useful in object location systems, especially where precision is required.
    • Used, for example, in medicine in computed tomography
    • Implementation based on our own algorithm written in C++.

Technologies used in the program

  1. Node.js
    • A JavaScript-based framework for building server-side web applications.
    • It works asynchronously, supporting real-time I/O operations.
  2. Frontend technologies
    • HTML, CSS, JavaScript and the Bootstrap framework.
    • They make it easier to create responsive and visually attractive interfaces.
  3. MongoDB database
    • Non-relational document-type database.
    • Flexible, scalable, used to store user and project data.
  4. External devices – BLEO System
    • Used for software testing.
    • It is based on Bluetooth technology for locating objects indoors.
    • Connection to sensors by entering the appropriate IP address in the program.

Program

The software runs as a web application, available by entering the appropriate URL. Once logged in, the user can create, manage, and measure projects online or offline.

Creating a project

  1. Determining the dimensions of the room and creating a field on the map.
    • Defining the dimensions of the location area.
    • Creating a graphical representation of a room.
  2. Marking the location of scanners, defining parameters.
    • Pinpoint sensor locations and determine their properties.
    • Configuration of measurement parameters.
  3. Saving the model in the database or on disk.
    • Possibility to save the created model in the MongoDB database or on a local disk.

Measurements – Edit page

  1. Editing the model, changing the position of walls and sensors.
    • Modification of project parameters based on real data.
    • Room model update.
  2. Choice of calculation method (trilateration, LBP, ILBP) or your own .exe file.
    • Possibility to choose the preferred calculation method for a given measurement.
    • Implementation of your own calculation method via an .exe file.
  3. Online or offline measurement, analysis of results.
    • Carrying out measurements in real time or based on previously saved data.
    • Analysis of measurement results and generation of reports.

Other functionalities

  • User registration and login using the JWT token.
    • Securing access to applications and user data.
  • List of created models, ability to export and import.
    • Viewing and managing created room models.
    • Import and export projects for easier sharing.
  • Implementation of a message and notification system.
    • Informing users about important events in the system.
    • Notifications about new measurements, design changes, etc.

Testing

I tested the software in laboratory conditions and in real rooms with various spatial configurations. The results were as expected, confirming the effectiveness of the trilateration method and the accuracy of the LBP and ILBP methods.

Conclusions

The software I developed is an effective and flexible platform for locating objects. Its modularity allows for easy adaptation to various user needs. The introduction of the possibility of uploading your own calculation methods additionally increases the potential of the program.

While working on the project, I consulted my supervisor, which significantly accelerated the development of the application. The knowledge received was crucial to the success of the work. I hope that my software will be used in practice and will contribute to the development of the field of object location.

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