For decades, India’s approach to cyclone management operated through fragmented structures that struggled to scale. The India Meteorological Department (IMD) served as the sole source of forecasting information, based on time series data released through formal channels that moved at deliberate pace rather than the immediate need for cyclone early warning system demand.
Line departments namely water resources, disaster management, agriculture, fisheries, and municipal authorities had operated in isolated silos, each with their own contingency protocols, communication channels, and decision-making processes. Information flowed linearly and often arrived delayed. Coordination was sporadic. There was a lack of integration of different departments in one common platform. This compartmentalization meant that critical intelligence rarely reached those who needed it the most, and decisions made in isolation often failed to account for interconnected impacts across sectors.
The cyclone creates a havoc situation for farmers, crop growth, water resource managers, reservoir operators, fishermen and vulnerable populations. The negligence in reporting and early warning alert would lead to greater catastrophes. Earlier, when cyclones struck, cascading failures followed: fishermen caught at sea received warnings hours too late. Agricultural extension officers couldn’t alert farmers in time to protect standing crops. Water resource managers lacked real-time reservoir data to make flood-prevention decisions. Municipal authorities operated with very less information in hand resulting in non clearance of drains, poor power network management, and absence of evacuation logistics across cities. Most tragically, the vulnerable populations- the elderly, pregnant women, persons with disabilities, and those in remote settlements, remained invisible to the system until disaster struck, leaving them with minimal time to seek safety or support. The above mentioned failures indicate that the system lacked the early warning system which would have necessitated early response.
This fragmented, reactive model persisted because alternatives seemed technologically impossible which can be due to lack of real time data, improper coordination and lack of technological intervention. Real-time data integration across departments would require massive infrastructure overhauls. Predictive accuracy beyond the IMD’s conventional forecasts seemed impossible. Reaching millions of citizens with targeted, real-time alerts in multiple languages across diverse geographies appeared operationally unfeasible.
Historically, Starting from year 2000 , several cyclones have hit the Andhra Pradesh, some of the major cyclones namely:
Table 1. Cyclones in AP since 2000:
Then came October 2025, and the Andhra Pradesh state changed the conversation.
Recognizing the fragility of India’s disaster management system, Vassar Labs partnered with the Andhra Pradesh Government to develop the AWARE system- not an incremental patch to existing systems, but a complete architectural reimagining of how governments detect, forecast, and coordinate responses to extreme weather events. More than a technological upgrade, AWARE 2.0 represented a philosophical shift: from reactive crisis management to proactive, data-driven governance. The platform’s name itself- AP Weather Forecasting and Early Warning Research Centre, captured this ambition to embed scientific intelligence into the state’s decision-making infrastructure as shown in Figure 1.
Figure 1 : The cyclone Montha in disaster management platform
At its core, AWARE 2.0 is a unified data-intelligence platform that dissolves the silos plaguing traditional disaster management. Rather than IMD being the sole information source, AWARE 2.0 ingests data from satellite feeds, meteorological sensors, drone networks, CCTV systems, mobile applications, WhatsApp governance channels, and citizen datasets as depicted in Figure 2. The above sources serves as an information that flows into a centralized Data Lake, a repository storing over 6 petabytes of real-time and historical data- which feeds into a Data Lens real time dashboard accessible simultaneously to the Chief Minister’s office, district collectors, mandal officials, and village secretariats.
Figure 2: Aware Platform
The technical architecture sounds elegant in theory but proved transformative in practice: when all departments access the similar real-time data, synchronized decision-making becomes possible. When forecasts are generated using AI and predictive analytics rather than relying solely on conventional meteorology, the probability of accuracy in the results improves. When alerts are automatically disseminated through multiple channels- SMS, WhatsApp, mobile apps, satellite information, millions of citizens receive warnings within minutes rather than hours. This helps in taking immediate action and favourable responses based on the alerts.
AWARE 2.0 is not a single-purpose tool but a comprehensive early-warning and decision-support ecosystem currently operating 28 live operational alert and advisory types, with 42 planned modules addressing multiple hazards. The modules of AWARE and its functions are shown in Table 2.
Table 2. Modules of AWARE 2.0 and its function:
Cyclone Montha: The Real-World Test of Early Warning Capabilities
When Cyclone Montha made landfall near Narsapuram on October 28-29, 2025, with sustained winds of 90-100 km/h and gusts reaching 110 km/h, Andhra Pradesh had its first major operational test for real-time disaster response powered by AWARE 2.0. The results vindicated the system’s architecture.
The platform detected and began tracking the cyclone up to 72 hours before landfall- a window that proved invaluable. Initial advisories were issued on October 27 (Day 1), triggering the first Common Alerting Protocol (CAP) and SMS alerts to 13 districts and potentially affected areas. When the cyclone’s path shifted on October 28 morning (Day 2), AWARE 2.0 automatically recalculated affected zones, rainfall intensity patterns, and wind severity forecasts, pushing revised advisories with updated risk assessments to collectors and secretariats within hours.
The system’s cyclone forecasting accuracy proved exceptional. AWARE 2.0 predicted wind speeds of 80-100 km/h at landfall; the observed maximum wind speed recorded at Machilipatnam reached 82 km/h, a validation of the platform’s predictive capabilities that conventional forecasting would have struggled to match.
The system didn’t just monitor; it orchestrated. Chief Minister N. Chandrababu Naidu conducted nine teleconferences between October 23-29, personally overseeing disaster management efforts. Officers across water resources, rural development, telecommunications, police, disaster management, agriculture, and municipal administration reported status updates based on real-time AWARE data systems as depicted in Figure 3. The tasks were assigned with geographic specificity, deadlines, and accountability- tracked minute by minute.
Figure 3: Departments benefited from AWARE Platform
Recognition and Replication: From Innovation to Policy
AWARE 2.0’s role in minimizing loss of life during Cyclone Montha did not escape the notice of state leadership. Chief Minister Chandrababu Naidu publicly recognized the system’s critical performance, acknowledging how real-time intelligence and coordinated action across departments transformed the state’s disaster response capabilities. This recognition positioned AWARE 2.0 not merely as a technological tool, but as a blueprint for how states could embed intelligence into their disaster management infrastructure.
The achievement gained traction in India’s media ecosystem. ETV Bharat featured extensive coverage of how AWARE technology enabled Andhra Pradesh to manage Cyclone Montha effectively as a real-time disaster response system. Metro India and other outlets reported on the “Cyclone Montha Fighters” felicitation ceremony, where Chief Minister Naidu presented mementoes and certificates to 137 officers and staff who displayed exemplary service during the cyclone, emphasizing their coordinated use of AWARE 2.0 and allied systems.
IT Minister Nara Lokesh and IT Secretary Bhaskar Katamneni publicly acknowledged AWARE 2.0’s critical contribution. Katamneni announced that all district-level RTGS centers would be operational by October-end, with Collectors directed to ensure timely completion of integration. He highlighted the creation of the centralized Data Lake storing over 6 petabytes of departmental data, integrated with the real-time Data Lens dashboard for seamless governance.
Why These Systems Matter: The Governance Paradigm Shift
AWARE 2.0’s success during Cyclone Montha reveals why integrated early-warning systems are becoming critical infrastructure in the age of climate change. Traditional disaster management treated extreme weather as discrete crises to be managed through reactive protocols. The AWARE system inverts this logic: it treats weather as continuous data to be analyzed in real time, enabling governance systems to shift from reactive crisis management to proactive resilience-building. The return period of any event acts as an important data for understanding its frequency and severity.
The platform demonstrates three transformative principles:
Unified Access to Real-Time Data Enables Coordinated Decision-Making
When key stakeholders – such as the Chief Minister, water resource secretaries, district collectors, mandal officials, and village secretariat staff, share access to the same real-time data, decision-making becomes cohesive rather than fragmented. Tasks that previously took weeks of coordination meetings are now accomplished in minutes through unified dashboards.
Empowering Citizens as Active Participants in Disaster Management
With 9.5 million citizens receiving targeted, actionable weather alerts on their phones, people move from being passive recipients to proactive agents of their safety. Over 12,000 grievances collected through crowdsourced feedback provide government officials with vital real-time intelligence reflecting ground realities that might otherwise remain unseen.
Technology Streamlines Governance by Reducing Bureaucratic Load
Traditional disaster management required large numbers of field officers to verify conditions and relay information. AWARE 2.0 compresses this process using drones, satellites, and citizen datasets. For example, 602 drones surveyed areas that would have taken thousands of officers days to cover, and real-time vehicle tracking replaced manual resource coordination, enabling faster and more efficient emergency response.
As climate change intensifies the frequency and severity of extreme weather events- cyclones, floods, droughts, heatwaves, states and nations are recognizing that conventional disaster management systems are insufficient. There needs to be an inclusion of various parameters such as wind speed, direction, sea state and storm surge alerts, cloud top temperature, nowcast along with wind and rainfall for accurate early warning systems and disaster management. Taking these into consideration, Andhra Pradesh’s experience during Cyclone Montha provides a blueprint for what governance looks like when data, technology, and human coordination converge around real-time intelligence.
Cyclones remain powerful natural phenomena. In October 2025, Andhra Pradesh transformed a potentially catastrophic weather event into a managed crisis where preparedness and rapid response saved lives,
The outcome was not that AWARE 2.0 prevented Cyclone Montha or eliminated all losses. Overall, AWARE enhanced flood disaster management by providing real-time, data-driven decision support that saved lives, mitigating risks, protected livelihoods and demonstrated how 21st-century governance should work. It optimized emergency response operations and effectively minimized social, economic, and environmental damages caused by flood events. It proved that when technology, governance, and human coordination converge around real-time intelligence, even the most powerful storms need not translate into human tragedy.
Client Name: Andhra Pradesh Disaster Management Authority
Area: Andhra Pradesh State
