• Bagal Navanath Shankar
• Dr. Rajesh Keshavrao Deshmukh
• Dr. Sandeep Kadam

Localization in wireless networks is crucial for various applications, including tracking, navigation, and surveillance. Traditional localization techniques, such as Received Signal Strength Indicator (RSSI), Time of Arrival (TOA), Time Difference of Arrival (TDOA), and Angle of Arrival (AOA), rely on physical layer measurements to estimate node positions. Despite their utility, these methods face significant limitations in isotropic environments due to factors like signal attenuation, multipath fading, synchronization issues, and hardware constraints. Recent advancements in Artificial Intelligence (AI) have introduced innovative solutions to enhance localization accuracy and robustness. AI-based approaches, including machine learning and deep learning algorithms, offer the potential to overcome the challenges faced by traditional methods by leveraging large datasets, adaptive algorithms, and advanced modeling techniques. This paper provides a comprehensive review of AI-enhanced localization techniques, examining their strengths, challenges, and applications in isotropic wireless networks. By synthesizing current research and identifying gaps, this review aims to highlight the transformative impact of AI on localization technologies and offer insights into future research directions.

Localization, Wireless Networks, Received Signal Strength Indicator (RSSI), Time of Arrival (TOA), Time Difference of Arrival (TDOA), Angle of Arrival (AOA), Artificial Intelligence (AI), Machine Learning, Deep Learning, Isotropic Environments, Localization Accuracy, Network Tracking.

"AI-Driven Localization Strategies in Isotropic Wireless Networks: An In-Depth Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 2, page no.f984-f991, February-2023, Available :http://www.jetir.org/papers/JETIR2302606.pdf

"AI-Driven Localization Strategies in Isotropic Wireless Networks: An In-Depth Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 2, page no. ppf984-f991, February-2023, Available at : http://www.jetir.org/papers/JETIR2302606.pdf