People with visual impairments face everyday challenges that limit their confidence and independence, especially in unfamiliar situations. The lack of obstacle detection technology suitable for specific requirements severely limits mobility and safety. Addressing this issue is essential to improving your quality of life, so you can navigate your surroundings safely and confidently. This research aims to promote accessibility for people with disabilities. We are solving human safety and mobility issues by developing an obstacle detection system using smartphones and Internet of Things (IoT) technology. The goal of the system is to provide accurate real-time information about obstacles such as bodies of water, allowing visually impaired people to navigate safely and independently. To identify obstacles and puddles in the user’s path, the intelligent system combines an ultrasonic sensor, an ESP32 microprocessor, and a smartphone app. ESP32 sensor analysis data allows you to find the right obstacles, smartphones can help visually impaired users by switching to a microcontroller that generates audio instructions. While the technology shows potential, constraints such as fine-tuning are required to improve accuracy and reduce false positives/negatives. Customizing the system to different user preferences and environmental conditions continues to be a problem in establishing a universally effective solution. Future studies will concentrate on improving the system’s obstacle detection skills through the use of powerful machine learning algorithms. In addition, efforts will be made to improve the hardware design for a more compact and user-friendly solution. Extensive field trials and user feedback will be required for the system to be further refined and widely implemented, ultimately improving the lives and confidence of visually impaired individuals in unfamiliar surroundings.