Aims: The goal of this dissertation is to develop and evaluate a smart drilling system designed to address ongoing challenges in orthopedic surgery related to angle and depth calculations. Current manual methods, which rely on visual estimation or depth calculations, frequently lead to errors. Such faulty estimations may then further lead to implant wastage, increased procedural time, and risks such as accidental radiation exposure both to the patients and surgeons. The proposed smart system is delivered using advanced sensors and WIFI enabled real-time feedback to overcome the shortcomings of such systems. This technology aims to enhance the precision of the surgeon and reduce subjective human judgments. In doing so, this study attempts to set a benchmark for the adoption of such technologies as standard tools in orthopedic surgery, aimed at improving patient outcomes while lowering operation costs and making the operating environment safer. Methods: Different stages of techniques in the research are applied, from innovative engineering design through software development to rigorous experimental validation. The initial phase was employed in designing and prototyping the smart drilling system. An already commercially available electric drill, Trixig, was modified for use as a platform for integrating advanced technological components. The principle of hardware design was based on the installation of an ESP32 microcontroller that supports wireless communication, and two critical sensors: a BNO085 IMU for angle measurement and an SLS130 linear potentiometer for tracking depth. Custom 3D-printed housings were manufactured from PETG filament using a high-precision 3D printer to house these parts properly, protect them, and make them compatible in a surgical environment. The study's second phase focused on software development. A bespoke application was programmed in C++ to process and display real-time feedback on angle alignment and drilling depth, offering visual aids to guide the surgeon during simulated procedures. This also includes an application for storing measurement data, which was used for further analysis and evaluation of the performance of the systems. Experimental validation was conducted in two stages: preliminary testing in a fully controlled laboratory condition and simulating surgical conditions with synthetic bone models to perform a test in a systematic way without the variability usually introduced with organic tissue. A series of experiments were designed to evaluate the system's performance in both angle and depth measurement. Measurements obtained using the smart drilling system were cross-validated using established methods, including a Vernier gauge for depth tracking and 3D imaging technologies—such as computed tomography (CT) and structured-light 3D scanning—to verify angular accuracy. The experimentation's last stage was devoted to comparative performance analysis. The smart system was, therefore, tested against conventional methods in estimating angles by the visual method and using manual depth gauges to assess improvement in precision and consistency. The advantage quantification of the system over conventional techniques was done with a view of paired t-tests, Shapiro-Wilk testing, and evaluation of mean absolute errors. The proposed paper has adopted a structured approach to present reproducibility and robustness that is necessary for the results. Results: When compared to traditional manual methods, the results demonstrated a significant improvement in accuracy and precision with the smart drilling system. The mean absolute errors for inclination angles of 30°, 45°, and 60° ranged between 0.6° and 1.3°. Compared to manual methods, this is a significant improvement as the errors recorded ranged from 1.9° to 4.5°. The system displayed mean errors of 0.35° ± 0.25° for inclination and 2° ± 1.33° for anteversion using reference angles of 45° for inclination and 20° for anteversion for combined measurements. The system's mean absolute error of 0.33 mm and standard deviation of 0.41 mm, which closely matched values acquired with a Vernier gauge, further demonstrated the extreme precision of the depth measurements. Apart from that, over-penetration was excellently monitored by the system, which is vital in preventing any soft tissue damage. The value of over-penetration, which was on average 5.5 mm ± 1.1 mm, matched the commonly achieved result by expert surgeons. From these results, the smart drilling system is able to reduce variability and increase orthopedic consistency during any surgical procedures. It is also reliable and effective. Conclusion: The conclusion of this dissertation emphasizes that the smart drilling system has the potential to alter orthopedic surgical practices by allowing modularity in design, capability for wireless operation, and real-time feedback, therefore increasing the accuracy and ease of use at low cost compared to expensive robotic systems. Thus, this minimizes implant waste, surgical time, and radiation exposure and thus provides considerable economic and patient care benefits to healthcare institutions. The system is designed to be compatible with the use of existing surgical tools; therefore, it flexibly extends current practices, which again reduces barriers to its adoption. Limitations of the study are stated accordingly. The experiments were conducted on synthetic bone models and the tests were performed by only one experienced surgeon. Consequently, future studies should be performed in cadaveric models, and a larger group of surgeons at various levels of experience should be used in order to further assess the generalizability and strength of this system. Further testing can also be done to see the capacity for the system's use in broadened surgical applications, such as minimally invasive techniques or specific orthopedic pathologies.