Unconventional Use Cases of AWS Services to Know In 2025

Tech Mar 4, 2025 76 Add to Reading List

It intrigues how technology flawlessly blends with everything around it and makes complex tasks easy. There are many reasons to hire AWS developers, cloud engineers, devops engineers, and other tech experts. Below we have mentioned five real-world scenarios where AWS services proved to be a boon for mitigating environmental disasters, wildlife conservation, smart agriculture, and whatnot. This is a step towards a more sustainable use of technical interventions.

1. AI-Powered Wildlife Conservation

Wildlife enthusiasts face challenges in keeping track of endangered species and mitigating poaching in remote wildlife areas. AWS provides tools to build an end-to-end wildlife monitoring system.

Data Collection: Use AWS IoT Core to link IoT-enabled cameras, motion sensors, and GPS collars on animals. These devices gather real-time data like images, videos, and location information. In areas with no internet and connectivity, AWS Snowball Edge transports data to the cloud.

Data Storage: Store raw data in Amazon S3, a scalable and cost-effective storage solution.

Data Processing: Use Amazon Recognition to check images and videos for species identification, behavior tracking, and poaching detection. Train custom machine learning models with Amazon SageMaker to improve accuracy.

Real-Time Alerts: Use AWS Lambda to trigger alerts when suspicious activity is noticed and inform rangers via Amazon SNS.

Visualization: Design dashboards with Amazon Quick Sight to visualize trends like animal population changes and migration routes. Forecast live data using Amazon Kinesis for real-time monitoring.

For example, the World Wildlife Fund (WWF) took advantage of AWS to be vigilant on elephants and rhinos in Africa, identifying individual animals and detecting poachers in real time.

2. Disaster Response and Emergency Communication

Technology becomes a rescuer when natural disasters hit the population; communication infrastructure often breaks down, leaving communities isolated. AWS helps keep communication and coordination disaster response efforts operating.

Temporary Communication Systems: Deploy AWS Snowball Edge devices to provide local computer and storage capabilities in disaster zones. Use Amazon Chime for secure voice and video conferencing among responders, and Amazon Connect to set up temporary call centers for emergency calls.

Data Management: Store real-time data such as survivor locations and resource availability in Amazon DynamoDB, a NoSQL database optimized for high-speed reads and writes. Automate workflows with AWS Lambda, such as sending alerts to rescue teams.

Disaster Mapping: Use Amazon Location Service to create interactive maps of affected areas, evacuation routes, and shelter locations. Generate dashboards with Amazon Quick Sight to display key metrics like the number of people rescued.

Public Alerts: Send mass notifications to affected populations using Amazon Pinpoint. Deliver emergency content quickly via Amazon CloudFront, a global CDN.

During Hurricane Maria in Puerto Rico, AWS helped restore communication networks and coordinate relief efforts, enabling efficient logistics and resource distribution.

3. Smart Agriculture with IoT

Farmers face challenges like water scarcity and inefficient resource allocation. AWS enables precision agriculture by leveraging IoT and analytics to optimize crop yields and reduce waste.

Sensor Deployment: Install IoT sensors in fields to monitor environmental factors like soil moisture, temperature, and humidity. Use AWS IoT Core to transmit data to the cloud and AWS Greengrass for edge computing to process data locally.

Data Storage and Processing: Store raw sensor data in Amazon S3 and query it efficiently using Amazon Timestream, a time-series database. Process data in real time with AWS Lambda to trigger actions like turning on irrigation systems.

Insights and recommendations: Train machine learning models with Amazon SageMaker to predict optimal planting times or pest outbreaks. Visualize trends and insights in dashboards using Amazon QuickSight.

Automation: Use the AWS IoT Rules Engine to define rules for automating tasks, such as watering crops when soil moisture drops below a threshold. Expose APIs for third-party integrations using Amazon API Gateway.

In arid regions like California, farmers have used AWS-powered systems to reduce water usage by up to 30% while increasing crop yields.

4. Space Exploration and Satellite Data Analysis

Satellite imagery is crucial for Earth observation, but processing large datasets can be computationally intensive. AWS streamlines satellite data acquisition, processing, and analysis.

Data Acquisition: Use AWS Ground Station to download satellite data directly into the AWS cloud, eliminating the need for expensive ground infrastructure. Store raw data in Amazon S3.

Data Processing: Process large datasets with Amazon EMR, a managed big data platform, or execute batch jobs with AWS Batch for tasks like image classification.

Machine Learning: Train machine learning models with Amazon SageMaker to classify satellite images, such as identifying deforestation or flooding. Use Amazon Rekognition for pre-trained models to detect objects or patterns.

Visualization: overlay satellite data on interactive maps using Amazon Location Service. Create dashboards with Amazon Managed Grafana to monitor trends like glacier retreat or sea-level rise.

NASA’s Earth Observing System Data and Information System (EOSDIS) uses AWS to store and process petabytes of satellite data and facilitates researchers to study climate change and natural disasters.

5. Crowdsourced Disaster Mapping

Maps are the guiding apparatus during emergencies; if they themselves are not accurate, they might pose a danger to the navigator, but it is labor-intensive doing it manually. AWS allows crowdsourcing and automation to create real-time disaster maps.

Crowdsourcing Data: Use Amazon Mechanical Turk to label and annotate disaster-related data, such as identifying flooded areas in satellite images. Provide volunteers with access to mapping tools via Amazon AppStream 2.0.

Data Processing: Stream real-time data into the system using Amazon Kinesis and process it with AWS Lambda to update maps dynamically.

Geospatial Analysis: Integrate geospatial data into interactive maps using Amazon Location Service. Query data stored in Amazon S3 with Amazon Athena for features like finding shelters within a specific radius.

Map Hosting and Distribution: Deliver maps and emergency content globally with Amazon CloudFront. Build and host a web application for viewing maps using AWS Amplify.

During the 2020 Beirut explosion, the disaster management team used AWS-powered platforms to spot the damaged areas, locate hospitals, and guide rescue teams, updating maps in real time as new information became available.

Conclusion

These five use cases show the variety of AWS services in addressing unconventional challenges. Whether conserving wildlife, responding to disasters, optimizing agriculture, exploring space, or mapping crises, AWS provides an array of tools to innovate and solve real-world problems effectively. By hiring AWS developers that can bring an agile ecosystem of services, organizations can solve complex issues with efficiency, scalability, and precision.

Now you may gauge the power AWS services hold based on these out-of-the-way applications. With an efficiently hired AWS developer, cloud engineer, or devops engineer, one can really solve any real-world problems and capitalize on solutions. Now it's your turn to make some moves; book a call with us to hire an AWS engineer.