Building AI-supported public safety and travel apps

The short answer

Public safety and travel apps help people stay informed and make decisions on the move: service disruptions, weather and road conditions, safe routes, local advisories, and ways to report problems. AI can improve them in specific, bounded ways:

• Summarising long or technical official notices into plain language, with a link to the source.
• Translating information for travellers and newcomers, including into local languages where verified translations exist.
• Answering questions about published information ("Is my route affected?").
• Sorting user reports so that staff see the most relevant ones first.

AI should not be the only source of safety-critical information, should not decide whether someone is in danger, and should never stand between a person and emergency services. The app should always make clear how to reach the official emergency line, and the number should be confirmed with the relevant authority before launch.

Where AI helps, and where it must not decide

The rule of thumb: AI can organise, explain and translate verified information. People and official sources remain responsible for safety decisions.

Ground answers in verified sources

Generative AI can produce confident but wrong answers. For safety and travel content, reduce that risk by design:

• Retrieve, then answer. Have the model answer only from a curated set of current, verified content (official alerts, schedules, advisories), and show the source with each answer.
• Show freshness. Display when the underlying information was last updated, and stop using stale data.
• Say "I don't know". Configure the assistant to decline when the answer is not in its sources, and point to the right official channel.
• Log and review. Keep records of questions and answers (with personal data minimised) so that errors can be found and fixed.

The NIST AI Risk Management Framework describes characteristics of trustworthy AI such as validity and reliability, safety, accountability and transparency, and explainability (NIST). They are a useful checklist for any organisation building AI features into an app, whatever its size.

Handle location data carefully

Location is what makes these apps useful, and it is also sensitive personal data.

• Ask only when needed. Request location when the user uses a location-based feature, and explain why.
• Prefer foreground access. Android distinguishes foreground location from background location, which needs a separate permission and is subject to Google Play policy (Android Developers). Apple's Core Location likewise asks users to authorise location use, with separate levels for use while the app is in use and at all times (Apple Developer Documentation).
• Accept approximate location. On Android, users can grant approximate rather than precise location, and the app should still work.
• Keep less for less time. Store location history only if there is a clear purpose, for a defined period.

In Nigeria, the Nigeria Data Protection Act 2023 (NDPA), enforced by the Nigeria Data Protection Commission (NDPC), applies to most apps that process personal data: you need a lawful basis such as consent, a clear purpose, data minimisation and appropriate security, and high-risk processing may call for a data protection impact assessment (NDPC). Public bodies and sector regulators may add their own requirements. This is general information, not legal advice.

Design for stress, not just convenience

People use safety apps when they are anxious, hurried or in poor conditions:

• Clear, calm language and large, obvious actions, including a visible way to reach emergency services.
• Accessibility. Follow WCAG 2.2, the current W3C Recommendation for accessible web content (W3C), and test with screen readers and large text.
• Local languages where the audience warrants it. Nigerian users may be more comfortable in Hausa, Yoruba, Igbo or Pidgin than in English, so consider verified translations of the most important content.
• Poor connectivity. Mobile data can be patchy or expensive, so cache recent alerts and key information so the app remains useful offline, and keep downloads small.
• Battery awareness. Avoid constant background location or heavy processing on the device, particularly on lower-cost phones and where charging is unreliable.

Test for failure, not just success

Before launch, test what happens when:

• the official data feed is late, empty or malformed;
• the AI service is slow or unavailable (the app should still show verified alerts without it);
• a user asks something outside the app's scope, including an emergency;
• a malicious user tries to make the assistant give harmful or false advice;
• many users open the app at once during a major event.

Design checklist

Limitations

AI models change, and their behaviour can shift after updates, so testing is ongoing rather than a one-time step. No design removes all risk of an incorrect answer, which is why verified sources, visible citations and human oversight matter more here than in most apps.

Next step

Our mobile app development service covers planning, design, build and testing for iOS and Android. For the AI components, see AI solutions and intelligent automation; for data protection questions, see data protection and compliance readiness.

Sources and further reading

Product capabilities and guidance change. These are the primary sources this article relies on, checked on the review date above.

1. Nigeria Data Protection Commission (NDPA and GAID 2025), Nigeria Data Protection Commission
2. AI Risk Management Framework, National Institute of Standards and Technology
3. Request location permissions, Android Developers
4. Requesting authorization to use location services, Apple Developer Documentation
5. Web Content Accessibility Guidelines (WCAG) 2.2, W3C

This article is general information, not legal, accounting or security advice for your specific situation. Examples are hypothetical unless stated otherwise.