An iot data-driven document tracking device with prescriptive analytics/ John Karlo C. Baniqued, Ma. Lilibeth A. Dela Cruz, Mildred R. Epan, Jhonn Wilfred F. Jusay, and Daniel M. Pelaez.--

Bachelor's thesis

College of Industrial Technology.-- Bachelor of engineering technology major in computer engineering technology: Technological University of the Philippines, 2025.

Includes bibliographic references and index.

In any organization, managing and processing documents has been a crucial part of an employee's
duties. These documents are essential for promoting accountability, consistency, and conformity to
company policies. As proof of their performance and excellence on campus, each employee at the
Technological University of the Philippines-Manila possesses DRA documents. Therefore, it is a
major setback if one of the documents is discovered to be missing, as this may result in delayed
salary. In order to address the problem of missing documents in workflow and to encourage
rigorous adherence to the Anti-Red Tape Authority's (ARTA) time limits, this study presents an
integrated hardware and software system called "An IoT Data-Driven Document Tracking Device
with Prescriptive Analytics" that is intended to effectively track physical documents pertaining to
ARTA-related school procedures. The system is built on an Internet of Things (IoT)-based
document tracking device that is physically linked to papers and tracks their movement and
progress throughout the workflow. The major goal is to solve inefficiencies and delays in document
processing by creating and testing a real-time tracking solution. The proposed system incorporates
an Arduino Nano 33 IoT microcontroller integrated with actuators, such as an active buzzer, a
vibration motor, and a linear actuating mechanism using a servo motor. The chassis of the device
was 3D printed using ABS plastic to ensure durability, customization, and improved spacing
between components. The Message Queuing Telemetry Transport (MQTT) protocol is used to
transmit data in real time, allowing the microcontroller and a Django-based web application to
communicate reliably. The web program also includes prescriptive analytics, which provide
actionable recommendations based on criteria such as lateness, delays, and processing time. The
system demonstrated accurate document tracking, progress monitoring, and real-time notifications
through comprehensive hardware and software testing. Evaluation results yielded an overall mean
score of 4.42, categorizing the system’s performance as “Very Satisfactory” and confirming its
reliability, functionality, and user acceptance.