Hyderabad Spacetech Experts Urge Faster AI Processing Of Satellite Data

Spacetech experts in Hyderabad have called for the urgent adoption of artificial intelligence (AI)-powered processing to convert vast amounts of satellite imagery into timely, usable intelligence, warning that underused data is currently delaying global climate action.

According to local industry leaders, the primary challenge in spacetech has shifted from collecting data to analyzing it. While satellites generate unprecedented volumes of images and measurements daily, much of this information remains underutilized, which limits its potential to improve disaster response, agriculture, climate monitoring, and urban planning.

Ronak Kumar Samantray, the founder and chief executive officer of the Hyderabad-based spacetech startup TakeMe2Space, explained that satellite data is being generated much faster than organizations can process it. He noted that raw satellite data must move through multiple stages—including ground station transfers, storage, calibration, processing, and interpretation—before it can reach end-users.

This workflow is further slowed down by limited computing capacity, high processing costs, fragmented platforms, a shortage of skilled analysts, and poor integration with government and enterprise systems.

Arunav Roy, senior vice president and market unit head at Cyient, a Hyderabad-based aerospace and defence engineering services firm, stated that the industry's focus must shift from simply collecting or storing imagery to converting it into decision-ready intelligence. Roy suggested that utilizing AI, GeoAI, and automation can help process images faster, detect environmental changes, identify risks, and generate predictive insights at scale.

The delays in processing have severe real-world consequences, particularly during natural disasters. Samantray pointed out that during floods, satellite imagery can identify inundated areas, damaged infrastructure, and blocked roads to guide rescue teams. However, if this information reaches emergency response teams several hours late, its practical value is lost.

Similarly, delayed data hinders agricultural planning. While satellite imagery can identify crop stress, soil moisture levels, waterlogging, pest-prone areas, and vegetation health, governments and farmers need this data early to make timely decisions.

Looking to the future, Samantray highlighted that advances in AI, cloud computing, and in-orbit processing could significantly reduce processing times. Instead of transmitting all raw datasets back to Earth, future satellites are expected to process information in space and transmit only the most relevant insights.