Why E911 Calls Sometimes Fail—and How AI is Transforming Emergency Call Reliability

In moments of crisis, every second counts. Emergency calls made through Enhanced 911 (E911) services are designed to connect people in distress to first responders quickly and efficiently. However, despite advances in telecommunications, E911 calls sometimes fail, delaying critical assistance. Network congestion, technical failures, and interoperability issues can all play a role in these failures. Fortunately, artificial intelligence (AI) is emerging as a powerful tool to enhance the reliability of emergency communications, ensuring that those in need receive immediate help.

E911 systems rely on sophisticated telecommunications networks to transmit accurate location data and call information to emergency dispatchers. However, network congestion during large-scale emergencies can prevent calls from going through. Technical malfunctions, such as errors in signal routing or equipment failures, can also hinder connectivity. Moreover, interoperability issues across different carriers and network providers can cause disruptions, particularly when calls are transferred between different systems.

Tharunika Sridhar, a distinguished expert in network engineering at T-Mobile, has firsthand experience addressing these challenges. As a key member of the Engineering Validation Team for WPS (Wireless Priority Services) and GETS (Government Emergency Telephony Services), Sridhar has worked to ensure that these critical communication services remain foolproof and resilient. "Ensuring that emergency calls are prioritized and function seamlessly during disaster situations is a crucial aspect of network engineering," says Sridhar.

E911 call reliability can be revolutionized by AI-driven technologies that prevent system failures before they happen. One of the key advancements is the use of AI-based predictive analytics, which can detect anomalies in network performance and prevent disruptions. These predictive systems analyze vast amounts of data in real time, identifying patterns that indicate potential failures and automatically deploying solutions.

In order to improve emergency phone services, Sridhar has helped T-Mobile integrate automation based solutions. By conducting over 50 test scenarios in lab environments and automating test setups, she has helped ensure the seamless integration of WPS/GETS with 4G LTE and 5G networks. This rigorous testing prevents network failures during critical emergency situations, making E911 systems more robust.

Another breakthrough in AI applications for emergency call systems is the implementation of machine learning algorithms to optimize network routing. These algorithms can dynamically reroute emergency calls in case of congestion or failure, ensuring that calls reach dispatchers without interruption. Additionally, edge computing—which processes data closer to the source rather than relying on centralized cloud systems—reduces latency, allowing emergency communications to function with greater speed and accuracy.

The integration of AI and next-generation telecommunication technologies is reshaping emergency communication strategies. Sridhar’s work on network reliability has extended beyond emergency call validation. Her contributions to the SCAM Likely project, which blocks fraudulent and spam calls, have provided insights into combating malicious robocalls that can clog networks and delay critical emergency communications. These efforts have reinforced the importance of AI-driven safeguards in ensuring reliable and secure telecommunications.

As 5G adoption continues to grow, network slicing is emerging as a game-changer for emergency services. This technology allows network operators to allocate dedicated resources for critical communications, preventing congestion and ensuring priority access for first responders. AI-powered self-diagnosing systems are also expected to enhance emergency call reliability by automatically detecting and resolving network issues in real time.

The future of E911 services will be driven by AI, edge computing, and predictive analytics. These innovations will enable telecommunications providers to deliver faster, more reliable, and fail-safe emergency communication systems. As network engineering professionals like Sridhar keep pushing the envelope, E911 call reliability will only increase, guaranteeing that assistance is always only a phone call away.