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Showing posts with label #TECHNOLOGY SECURITY. Show all posts
Showing posts with label #TECHNOLOGY SECURITY. Show all posts

Tuesday, 22 September 2026

"India's Contemporary Security Challenges: Operation Sindoor and the Expanding Role of Forensic Science in National Security."----ADDRESS BY BRIGADIER HEMANT MAHAJAN, YSM Meraki 4.0 – Forensic Science Week Department of Forensic Science, School of Science Sandip University, Nashik 30 September 2026

 

 


Respected Vice Chancellor, Dean, Faculty Members, Distinguished Guests, and my young friends from the Department of Forensic Science,

Good morning.

It is a great pleasure and privilege to be here today at Sandip University during "Meraki 4.0 – Forensic Science Week."

I have spent over four decades in uniform, serving in some of India's most challenging operational environments—from counter-insurgency operations in Jammu & Kashmir to national security planning and military education. During these years, I have seen battles fought with guns, artillery, tanks, and missiles.

However, I have also seen battles won not by weapons alone but by evidence, analysis, intelligence, and scientific investigation.

That is where all of you come in.

When people think about national security, they imagine soldiers standing on the border, fighter aircraft in the sky, warships at sea, or missiles protecting the nation.

But very few realize that behind every successful counter-terrorist operation, every conviction of a terrorist, every exposure of a spy network, every cybercrime investigation, and every detection of fake news campaigns, there is often a forensic scientist quietly working behind the scenes.

Therefore, today's topic is:

"India's Contemporary Security Challenges: Operation Sindoor and the Expanding Role of Forensic Science in National Security."

 

The Changing Nature of Security

When I joined the Indian Army in 1975, threats largely came from identifiable enemies across the border.

Today, the situation is far more complex.

India faces:

  • Terrorism
  • Cross-border infiltration
  • Cyber attacks
  • Deepfakes and AI-generated disinformation
  • Drug trafficking
  • Narco-terrorism
  • Radicalization through social media
  • Economic warfare
  • Espionage
  • Information warfare
  • Hybrid warfare

The battlefield is no longer limited to land, sea, and air.

Today the battlefield includes:

  • Mobile phones
  • Social media platforms
  • Computer networks
  • Financial systems
  • Human minds

In this new environment, forensic science has become a frontline national-security discipline.

 

Operation Sindoor – Lessons Beyond the Battlefield

Operation Sindoor demonstrated India's determination and capability to respond decisively to terrorist threats and hostile actions.

However, after every operation comes another challenge.

Who planned the attack?

Who financed it?

Who supplied explosives?

Which communication networks were used?

Who spread propaganda?

Who created false narratives?

Who attempted to manipulate public opinion?

These questions cannot be answered by soldiers alone.

They require forensic experts.

The soldier may neutralize a terrorist.

The forensic scientist helps neutralize the entire network behind him.

 

Why Forensic Science Matters to National Security

Many students believe forensic science is limited to crime scenes and fingerprints.

That perception is outdated.

Today forensic science contributes to:

Counter-Terrorism

After a terrorist attack investigators examine:

  • Explosive residues
  • DNA evidence
  • Ballistic signatures
  • Mobile phones
  • Digital devices
  • GPS data

A tiny fragment recovered from a blast site can reveal an entire terrorist network.

 

Cyber Forensics

Today's terrorists and hostile intelligence agencies operate online.

Cyber forensic experts investigate:

  • Hacked systems
  • Encrypted communications
  • Dark web activities
  • Cryptocurrency transactions
  • Malware attacks

The next major attack on India may begin with a keyboard rather than a rifle.

 

Social Media and Deepfake Forensics

This is an area that will directly affect your generation.

Artificial Intelligence can now create:

  • Fake videos
  • Fake speeches
  • Fake photographs
  • Fake voice recordings

Imagine a fake video appearing during a national crisis showing a senior military commander making inflammatory statements.

Within minutes it could trigger panic.

Forensic specialists are becoming the defenders of truth.

You are not merely analyzing images.

You are protecting national stability.

 

Financial and Economic Forensics

Modern terrorism requires funding.

Forensic accounting helps uncover:

  • Money laundering
  • Terror financing
  • Hawala networks
  • Illegal foreign funding

Following the money often leads investigators to the masterminds.

 

The Forensic Scientist as a National Security Professional

Many of you may not wear uniforms.

But that does not mean you cannot serve the nation.

National security today requires:

  • Soldiers
  • Police officers
  • Intelligence professionals
  • Cyber experts
  • Data scientists
  • Forensic specialists

Every one of them contributes to national security.

A forensic scientist who identifies a terrorist bomb-maker has contributed as much to national security as the soldier who captures him.

 

A Lesson from Counter-Insurgency Operations

During my service in Jammu & Kashmir, we often recovered seemingly insignificant items:

  • A battery
  • A handwritten note
  • A map
  • A SIM card
  • A piece of wire

To an ordinary person these were useless objects.

To investigators they became critical evidence.

Many operations succeeded because someone patiently analyzed tiny clues.

National security often depends on details.

And forensic science is the science of details.

 

Humorous Forensic Anecdote No. 1

People often tell me:

"Sir, we watch crime serials. Forensic scientists solve every case in thirty minutes!"

I tell them:

"If that were true, India's police stations would be empty and forensic laboratories would be producing miracles every evening at 9 PM."

Real forensic science is not magic.

It is patience, science, and hard work.

Unfortunately, evidence does not cooperate with television schedules.

 

Humorous Anecdote No. 2

A student once asked a forensic expert:

"Sir, can fingerprints lie?"

The expert replied:

"No. But the person leaving them behind usually does!"

That is why forensic science is so powerful.

Evidence is often more reliable than human memory.

 

Humorous Anecdote No. 3

In the Army we often say:

"An officer may forget where he kept a document."

"But forensic experts will eventually discover where he touched it!"

That is why I always treat forensic scientists with great respect.

You can find things people desperately hope nobody finds.

 

Future Challenges

As you enter the profession, prepare yourselves for emerging threats:

Artificial Intelligence Forensics

Identifying AI-generated content.

Drone Forensics

Recovering information from hostile drones.

Space and Satellite Data Analysis

Using geospatial evidence.

Digital Evidence Authentication

Verifying the authenticity of images and videos.

Cognitive Warfare Investigation

Detecting organized influence operations and information manipulation.

The future forensic laboratory will look very different from today's laboratory.

It will combine:

  • Artificial Intelligence
  • Big Data Analytics
  • Cyber Investigation
  • Behavioural Analysis
  • National Security Studies

 

My Message to Students

My young friends,

India is entering an era where security challenges are becoming increasingly complex.

The nation will require professionals who can think scientifically, analyze objectively, and act ethically.

Always remember:

A soldier protects the nation's borders.

A forensic scientist protects the truth.

And in national security, truth is often the most powerful weapon.

You may not stand at the Line of Control.

You may not fly a fighter aircraft.

You may not command a warship.

Yet your work may prevent a terrorist attack, expose a cyber intrusion, identify a spy, uncover a deepfake campaign, or help convict those who seek to harm our nation.

That is national service of the highest order.

 

Conclusion

As I conclude, I would like to leave you with a simple thought:

"In the 21st century, every crime scene is a source of intelligence, every digital device is a potential battlefield, every piece of evidence is a strategic asset, and every forensic scientist is a guardian of national security."

I wish all of you great success in your careers and hope many among you will contribute to making India safer, stronger, and more secure.

Thank you.

Jai Hind!

Monday, 24 August 2026

The Historic Transfer-On 10 September 2025, ISRO handed over the entire Small Satellite Launch Vehicle (SSLV) to Hindustan Aeronautics Limited (HAL)

 

ЁЯЪА 

On 10 September 2025, ISRO handed over the entire Small Satellite Launch Vehicle (SSLV) to Hindustan Aeronautics Limited (HAL) — the first time a space agency has given a complete rocket to a company. HAL won the contract worth ₹511 crore, beating two other consortia. The goal: let ISRO focus on advanced projects like Gaganyaan, while industry manages routine satellite launches.

ЁЯУЕ The Two-Year Timeline

HAL gets drawings, two years of joint work with ISRO engineers, and two rockets to build. After that, HAL must operate independently under a non-exclusive licence. The concern: transferring a decade of ISRO’s experience in just 24 months may be unrealistic.

✈️ Lessons from HAL’s Past

  • Su-30MKI Fighters (2004–2020): HAL licence-built 222 jets with Russian kits. Indigenous content was only 13% (vs. 60% promised), and expertise failed to take root.

  • Dhruv Helicopter (1984 onwards): Joint design with German engineers gave HAL genuine design capability. ЁЯСЙ The difference: design knowledge sharing vs. mere assembly.

ЁЯза The Challenge of Tacit Knowledge

Rocket programmes rely heavily on unwritten, experiential knowledge — why a weld angle matters, or which vibration signals danger. This cannot be captured in manuals. Transfer depends on absorptive capacity — the receiving firm’s ability to understand and internalize knowledge.

ЁЯМН Global Case Studies

  1. Toyota (NUMMI Plant, USA): Success came from embedding workers in Japan and long-term collaboration. Manuals alone failed.

  2. Japan (F-15J to Sixth-Gen Fighter): Used licence production as a training ladder over decades.

  3. South Korea (F-16 to KF-21): Progressed step by step, co-developing with Lockheed Martin, eventually mastering radar technology.

  4. NASA & SpaceX (2006 onwards): NASA placed engineers inside factories, shared decades of failure data, and stayed engaged — enabling SpaceX’s rapid success.

ЁЯФС Common Success Factors

Across industries and countries, successful transfers required:

  • Years of joint work, not months

  • Sequential programmes building on each other

  • Supplier presence long after handover

ЁЯЗоЁЯЗ│ The Open Question for India

The SSLV agreement gives HAL two years of joint work, then nothing more. ISRO spent over a decade developing SSLV, including failures and redesigns. HAL risks missing the tacit knowledge unless ISRO treats this as the first stage of a longer partnership, continuing support like NASA did with SpaceX.

ЁЯОп Conclusion

India’s decision to transfer SSLV is strategically sound. But the two-year limit may be insufficient. For HAL to truly master rocket-building, ISRO must remain engaged beyond the initial handover — otherwise, India risks repeating past mistakes of “assembly without design.”

Sunday, 2 August 2026

Algorithms: Powerful Tools for Engineering an Invisible Coup written byLt Gen Abhay Krishna, PVSM, UYSM, AVSM, SM(G), VSM, ADC, (Retd) Former Army Commander of South Western, Eastern and Central Army Commands of Indian Army., August 2, 2026

 

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India’s young citizens are being shaped by social‑media algorithms that amplify emotion and polarisation, creating conditions for an “invisible coup” unless the state urgently regulates platforms, fixes social grievances, and builds its own powerful counter‑narratives.


India’s Gen Z: A Vast, Always‑Online Cohort

India now has about 407 million people aged 14–29, roughly 28% of the population, forming the world’s largest youth generation and a decisive future voter base. This is the first Indian generation that has lived entirely in an internet‑saturated world, with screens and ranking systems as their main window to reality. Studies show they spend many hours daily on devices, much of it on social media, meaning algorithms now strongly influence what they see, feel and believe.


How Algorithms Manipulate Emotion and Reality

Social‑media algorithms are optimised to maximise engagement and advertising revenue, not truth or social health. They privilege anger, fear and outrage over calm, nuanced information, turning feeds into sequences of emotional triggers rather than balanced views of reality. As a result, these platforms distort public debate, suppress inconvenient facts, and become extraordinarily efficient propaganda tools that amplify the most emotionally charged versions of any story.


Global Evidence of Algorithmic Political Power

The article cites multiple global episodes to show how ranking systems shape real‑world politics. In the US, platform handling of the Hunter Biden laptop story raised concerns that information was “managed” under internal and external pressure, while Meta has been accused of letting its systems fuel anti‑Rohingya hate and violence in Myanmar, as later noted by UN and Amnesty investigations. Earlier, during the Arab Spring, Western militaries used sophisticated “sock puppet” software to run multiple fake personas and steer online conversations, proving that those who control ranking systems can influence the “emotional weather” of entire populations.

South Asian Flashpoints and India’s NEET Protests

Similar algorithm‑driven dynamics are now visible in South Asia, from Nepal and Bangladesh to India. In Nepal, a 2025 social‑media ban triggered a Gen Z uprising coordinated through TikTok, Discord and other platforms, where viral hashtags converted resentment into rapid street mobilisation that toppled the prime minister. In India, NEET paper leak protests were intensified by Instagram Reels, AI‑generated videos, deepfakes and influencer networks, with emotional clashes with police being algorithmically boosted, outpacing traditional media and institutional messaging.

Algorithmic Capture as a Strategic Threat

Across cases—from US controversies to Myanmar, the Arab Spring, Nepal, Bangladesh and NEET—the same pattern emerges: proprietary ranking systems drive attention based on engagement, not truth or social consequence. For India, this is particularly dangerous because these systems now sit at the centre of political life for nearly 400 million young citizens, giving corporations like Meta a quantum of soft power that no democratic government has effectively constrained. The author warns that this “algorithmic capture” of youth threatens public opinion integrity, social stability and electoral processes.

A Strategy of Control Without Crude Bans

The article argues that outright bans on platforms like Meta or Google would provoke youth resistance and heavy political costs. Instead, it recommends a gradual, indirect strategy of digital control using legal ambiguity, economic leverage, infrastructure dependence and narrative framing rather than open confrontation. The government should shape platform behaviour by tightening rules and compliance obligations instead of trying to switch social media off altogether.

Key Regulatory and Data‑Control Measures

First, the state should impose rules on platforms and intermediaries to remove content swiftly on official directions and comply with local regulations under the banners of sovereignty, public order, child safety or anti‑misinformation. Second, data localisation should be mandated, requiring user data and algorithm‑training inputs to be stored in India so that law‑enforcement and intelligence agencies can access them under national security or public‑order laws. The author suggests that step‑by‑step regulation, data rules, tax measures, audits, and licensing tied to algorithmic transparency and user‑data audits can gradually bring platforms under national control.

Learning from China, Russia and Turkey

The article urges India to study and selectively adapt models from other states already asserting strong digital sovereignty. China’s cybersecurity and data‑security laws represent a strict model, while Russia’s data localisation and Turkey’s requirements for social‑network providers are seen as softer variants. By threatening fines, ad restrictions or operational disruption, governments can force platforms to set up local data centres and compliance teams, which then become the gateway for negotiating ranking preferences, “positive energy” content quotas and down‑ranking of sensitive topics—without announcing explicit bans.

Two‑Pronged Response: Fix Grievances and Build Counter‑Algorithms

At the highest level, the author proposes a two‑pronged strategy. First, governments must proactively identify and address genuine social grievances—such as repeated exam leaks, crimes against students, perceived ideological bias in curricula, inadequate job creation and corporate exploitation of youth—because unresolved issues give foreign and hostile actors credible narratives to weaponise. Second, the state must invest in sophisticated “counter algorithms”: technology‑driven, coordinated efforts to push corrective and stabilising narratives across digital media, matching adversaries in both scale and sophistication.

Building Capacity, Oversight and Narrative Power

Implementing this strategy is difficult because it demands administrative alertness, sincerity and coordination across Union and States, while the digital domain is dominated by superpowers with guarded resources. Nonetheless, India’s strong technical talent pool can be mobilised with focused policy, dedicated resources, and institutional mechanisms for algorithmic oversight. The author also calls for taxation, periodic large‑scale audits, licensing and registration requirements, and massive production of preferred narratives through official channels and aligned influencers to counter fake videos and provocative misinformation.

Preventing an Invisible Coup Over India’s Youth

In conclusion, the article warns that algorithms already command hours of daily attention from hundreds of millions of young Indians and decide which anger or hope becomes visible and which facts are buried. This is described as “engineered consent” masquerading as convenience, allowing unelected platform owners to shape the next generation of voters, leaders and soldiers. If India fails to reclaim its information environment, an “invisible coup” could occur without any shots fired, as a whole generation grows up believing a reality curated by ranking systems serving hidden commercial or geopolitical interests—a future no sovereign nation can accept without a fight.

Wednesday, 29 July 2026

“How One Marine Colonel Forced AI Into America’s Wars, And What Project Maven Reveals About India”

 


 Origins of Project Maven

  • Initiated in 2017 by Marine Colonel Drew Cukor after witnessing AlphaGo’s victory over a human champion.
  • Inspired by the idea that human + machine collaboration outperforms humans alone.
  • Aim: integrate AI into US military operations to close the gap between firepower and poor information systems.

The Problem: Data Chaos

  • US forces relied on Microsoft Office tools and fragmented defence software, often unreliable in combat.
  • Example: GPS reset error in Kandahar (2001) led to friendly fire casualties.
  • Cukor concluded: America collected vast data but failed to use it effectively.

Building Maven

  • Officially named Algorithmic Warfare Cross-Functional Team.
  • Initial funding: $40.8M scavenged from Pentagon reserves.
  • Recruitment: Marine reservists for grit, startups for innovation.
  • Strategy: horse racing model – multiple startups competing on 90-day cycles.
  • Resistance: Air Force, Marine Corps, and Google employees opposed AI weaponisation.

Industry Partnerships

  • Startups like Clarifai shifted from wedding photo recognition to drone footage analysis.
  • Google withdrew after employee protests; Microsoft, Amazon, and Palantir stepped in.
  • Palantir revived through Maven, later becoming a top defence contractor.

 Field to Learn Doctrine

  • AI deployed before maturity → improved through real-world use.
  • Early failures in Somalia (2017) corrected by retraining models.
  • Ukraine war (2022): rapid retraining boosted accuracy, compressing the kill chain from <100 to >1,000 targets/day.
  • By integrating large language models, targeting capacity increased fivefold.

Internal Resistance

  • Pentagon culture resisted “broken software” deployment.
  • Cukor faced investigations and reprimands, ending his career as colonel.
  • His wife noted: “Every Marine learns the Corps will never love you back.”

China Factor

  • Fear of losing to China drove Maven.
  • China adapted US concepts, compelled tech firms to cooperate, and fielded capabilities faster (7 years vs US 16 years).
  • As Cukor said: “If you want to see the cutting edge of AI, you go to Shanghai.”

Lessons for India

  • Industry gap: India lacks Silicon Valley-scale AI firms; defence sector relies on DRDO, PSUs, and imported kit (“screwdriver-giri”).
  • Acquisition gap: Defence Acquisition Procedure (2020) too slow; startups die between prototype and production. iDEX/ADITI funding too small (Rs 450 crore).
  • Cultural gap: India’s military is risk-averse, zero-defect, unlike US willingness to field immature AI.
  • Data gap: Indian military still digitising legacy paper records; fragmented and siloed.

Conclusion

  • Maven shows what preconditions are needed:
    • Industry base for AI.
    • Procurement flexibility.
    • Tolerance for failure.
    • Structured, accessible data.
  • India is “not yet in the room” – still building foundations before it can ask the deeper question: “Are we the best custodians of this tech?”

Palantir’s Origins and Core Idea-'why doesn't India have its own Palantir?

 


  • Founded in 2003 with CIA venture arm funding.
  • Built to solve intelligence failures caused by fragmented data systems (post-9/11).
  • Core product: an ontology layer that integrates disparate databases into a coherent model.
  • Platforms: Gotham (defence/intelligence) and Foundry (commercial/civilian use).

Founding Story and Philosophy

  • Name inspired by Tolkien’s Palant├нri (seeing-stones).
  • Co-founders included Peter Thiel, Nathan Gettings, Joe Lonsdale, Stephen Cohen, and Alex Karp (philosopher turned CEO).
  • Early funding: $30M from Thiel + $2M from CIA’s In-Q-Tel.
  • Strategy: forward-deployed engineers embedded in client organisations, not traditional sales teams.
  • Karp’s leadership style: blunt, philosophical, openly moral about war and national survival.

Gotham in Action

  • Used by LAPD for predictive policing (Operation LASER) → later criticised for bias.
  • ICE’s FALCON system predicted worker behaviour ahead of raids.
  • In Ukraine, Gotham integrates battlefield data for AI-assisted targeting.
  • Pentagon’s Project Maven expanded Palantir’s role in military AI.
  • Civilian contracts (e.g., NHS UK) face suspicion due to Palantir’s security-state image.

Business Model and Growth

  • Revenue surged 85% YoY to $1.633B (latest filings).
  • $10B, 10-year US Army contract consolidating 75 prior deals → near-permanent lock-in.
  • Palantir seen as infrastructure, not just software.
  • Controversy: building cross-agency citizen databases raises governance concerns.

Preconditions for Success

  1. US state’s willingness to trust private contractors.
  2. Tolerance for controversy in exchange for capability.
  3. Patient, high-risk capital (17 years of losses before IPO).
  4. Outsourcing cognitive functions (decision-making) to private vendors.

 The India Question

  • India lacks a Palantir-scale defence data integrator.
  • Defence innovation (iDEX) remains small-scale (Rs 500 crore budget).
  • India’s Digital Public Infrastructure (DPI) (Aadhaar, UPI) shows a different model: state-owned rails, not vendor dependency.
  • US chose vendor lock-in; India chose public ownership for long-term control.

 Barriers in India

  • Defence data fragmentation across Army, paramilitary, police, and agencies.
  • Procurement: project-based tenders favour low-risk bidders.
  • Weak vendor qualification and oversight → history of defective components.
  • Cultural mistrust between state and private sector.

What Needs Fixing

  • Procurement trust: long-term enterprise agreements, accountability, rigorous qualification.
  • Capital: India lacks an In-Q-Tel equivalent; needs sovereign VC-style fund (NIIF/SIDBI could evolve).
  • Mission orientation: India’s top engineers prefer consumer internet/SaaS over defence-tech due to slow payments and opaque rules.

 Conclusion

  • Palantir thrived because the US tolerated dependency on private vendors for speed and capability.
  • India’s model prioritises sovereign control of digital infrastructure.
  • For India to build Palantir-like defence capability, it must reform procurement, capital funding, and trust in private vendors.
  • Without these, India’s defence-tech ecosystem will remain fragmented and underpowered.

Monday, 20 July 2026

India's New Leap in the Space Sector: Vikram-1, the Exit of ISRO Scientists, and Future Challenges Introduction


Two significant developments have recently taken place in India's space sector. The first is the successful launch of the Vikram-1 rocket, developed by the Indian private startup Skyroot Aerospace, and the second is the discussion surrounding the departure of nearly 120 scientists from ISRO. These developments have sparked a broader debate about the current state of India's space sector, as well as its future direction, opportunities, and challenges.

Skyroot Aerospace was founded and is led by former ISRO scientists Pawan Kumar Chandana and Naga Bharath Daka.

 

Vikram-1: A Historic Milestone for India's Private Space Sector

The successful launch of the Vikram-1 rocket, developed by Hyderabad-based startup Skyroot Aerospace, established in 2018, marks the beginning of a new era in India's space industry. Remarkably, the average age of the scientists and engineers behind this project was only 20 to 25 years, highlighting the capabilities, innovation, and entrepreneurial spirit of India's younger generation.

Today, more than 400 startups are actively working in India's space technology sector. This clearly indicates the emergence of a broad space ecosystem extending well beyond ISRO.

 

Space Technology: The Essential Infrastructure of the Future

A key point raised during discussions was that just as the internet has become an indispensable part of daily life, space technology will become a fundamental necessity in the future.

Weather forecasting, agricultural planning, defence, education, telecommunications, disaster management, and navigation all depend heavily on satellite technology. Therefore, space research is no longer merely a matter of national prestige; it is a cornerstone of national development.

 

Departure of 120 ISRO Scientists: Crisis or Natural Evolution?

The news of approximately 120 scientists leaving ISRO attracted considerable attention. However, rather than viewing it solely as a crisis, it should also be seen as a natural process within a growing industry.

Higher salaries, better research facilities, faster decision-making processes, and greater opportunities in the private sector have encouraged many scientists to join private companies. Such talent migration is common in technology and research sectors worldwide.

While this may cause temporary delays in certain projects, there is no reason to conclude that it poses a serious threat to India's overall space programme.

 

India's Position in the Global Space Race

India aims to conduct approximately 13 launches annually. In comparison:

  • China conducts around 100 launches per year.
  • The United States conducts more than 200 launches annually.

As India emerges as the world's fourth-largest economy, a corresponding increase in investments and launch capabilities in the space sector is both expected and necessary.

 

America's Success and the Role of Private Enterprise

The success of the United States in space is not driven solely by NASA. Private companies such as SpaceX, Blue Origin, and Rocket Lab have played a transformative role.

Similarly, India is witnessing the rise of companies such as Skyroot Aerospace, Agnikul Cosmos, Pixxel, Dhruva Space, and GalaxEye.

As a result, ISRO's role is gradually evolving from being the country's sole space organisation to becoming a mentor, enabler, and regulator of a broader space ecosystem.

 

Reusable Rockets and Declining Launch Costs

Reusable rocket technology is dramatically reducing the cost of launching satellites.

  • A few years ago, sending one kilogram of payload into orbit cost approximately $55,000.
  • Today, that cost has fallen to only a few thousand dollars.
  • In the coming decade, it may fall below $100 per kilogram.

This trend is likely to accelerate the commercialisation of space activities worldwide.

 

Major Challenges Before ISRO

1. Retaining Talent

ISRO now faces competition from world-class private companies. It must improve compensation, research facilities, and career opportunities to retain top talent.

2. Bureaucratic Delays

Unnecessary administrative interference in scientific decision-making needs to be minimized. Research projects often face delays during approval processes.

3. Lack of Succession Planning

ISRO must ensure that trained replacements are available for scientists occupying critical positions.

4. Insufficient Research Investment

India's annual space budget is approximately $1.6 billion. In comparison:

  • China: Approximately $20 billion
  • United States: More than $25 billion

The funding gap remains substantial.

 

The Need to Develop a Scientific Culture

Scientists in India often do not receive the level of social recognition accorded to cricketers or film stars.

There is a need for successful missions such as Vikram-1 to be discussed widely in schools and universities, inspiring students to pursue careers in science and technology. Scientific achievements should become a matter of national pride and public celebration.

 

The Future Space Economy

According to experts, the next decade will witness rapid growth in:

  • Space tourism
  • Space-based manufacturing
  • Pharmaceutical research in space
  • Satellite internet services
  • Lunar and Martian industries

The convergence of space technology and the internet is expected to form the foundation of the next global economic revolution.

 

The Way Forward for India

To accelerate the growth of India's space sector, the following measures are essential:

  1. Significantly increase funding for space research.
  2. Improve salaries, incentives, and facilities for scientists.
  3. Reduce bureaucratic hurdles in decision-making.
  4. Encourage greater participation by private industry.
  5. Expand science and technology education.
  6. Strengthen the culture of research and innovation.
  7. Enhance national recognition and appreciation of scientists.

 

Conclusion

The success of Vikram-1 is not merely the achievement of a startup; it marks the beginning of a new era in India's space journey. While the departure of some ISRO scientists is a matter of concern, it is also a reflection of increasing competition and the expansion of India's space industry.

India's future in space will not depend solely on ISRO. The combined efforts of ISRO, private enterprises, startups, research institutions, and young scientists can transform India into a global space power. Vikram-1 represents the first significant step in that direction, and the coming decade is likely to be decisive for India's emergence as a leading space-faring nation

рднाрд░рддाрдЪ्рдпा рдЕंрддрд░ाрд│ рдХ्рд╖ेрдд्рд░ाрддीрд▓ рдирд╡ी рдЭेрдк : рд╡िрдХ्рд░рдо-1, рдЗрд╕्рд░ोрддीрд▓ рд╡ैрдЬ्рдЮाрдиिрдХांрдЪे рдиिрд░्рдЧрдорди рдЖрдгि рднрд╡िрд╖्рдпाрддीрд▓ рдЖрд╡्рд╣ाрдиे

 


рдк्рд░рд╕्рддाрд╡рдиा

рднाрд░рддाрдЪ्рдпा рдЕंрддрд░ाрд│ рдХ्рд╖ेрдд्рд░ाрдд рдЕрд▓ीрдХрдбे рджोрди рдорд╣рдд्рдд्рд╡ाрдЪ्рдпा рдШрдЯрдиा рдШрдбрд▓्рдпा. рдкрд╣िрд▓ी рдо्рд╣рдгрдЬे рд╕्рдХाрдпрд░ूрдЯ рдПрд░ोрд╕्рдкेрд╕ рдпा рднाрд░рддीрдп рдЦाрдЬрдЧी рд╕्рдЯाрд░्рдЯрдЕрдкрдиे рд╡िрдХрд╕िрдд рдХेрд▓ेрд▓्рдпा рд╡िрдХ्рд░рдо-1 рд░ॉрдХेрдЯрдЪे рдпрд╢рд╕्рд╡ी рдк्рд░рдХ्рд╖ेрдкрдг, рддрд░ рджुрд╕рд░ी рдо्рд╣рдгрдЬे рдЗрд╕्рд░ोрдордзीрд▓ рд╕ुрдоाрд░े 120 рд╡ैрдЬ्рдЮाрдиिрдХांрдиी рд╕ंрд╕्рдеेрддूрди рдмाрд╣ेрд░ рдкрдбрд▓्рдпाрдЪी рдЪрд░्рдЪा. рдпा рджोрди्рд╣ी рдШрдЯрдиांрдиी рднाрд░рддीрдп рдЕंрддрд░ाрд│ рдХ्рд╖ेрдд्рд░ाрдЪ्рдпा рд╡рд░्рддрдоाрди рд╕्рдеिрддीрдмрд░ोрдмрд░рдЪ рднрд╡िрд╖्рдпाрддीрд▓ рджिрд╢ा, рд╕ंрдзी рдЖрдгि рдЖрд╡्рд╣ाрдиे рдпांрдмाрдмрдд рд╡्рдпाрдкрдХ рдЪрд░्рдЪा рд╕ुрд░ू рдХेрд▓ी рдЖрд╣े.

рд╕्рдХाрдпрд░ूрдЯ рдПрд░ोрд╕्рдкेрд╕рдЪी рд╕्рдеाрдкрдиा рдЗрд╕्рд░ोрдЪे рдоाрдЬी рд╢ाрд╕्рдд्рд░рдЬ्рдЮ рдкрд╡рди рдХुрдоाрд░ рдЪंрджрдиा рдЖрдгि рдиाрдЧा рднрд░рдд рдбाрдХा рдпांрдиी рдХेрд▓ी рдЕрд╕ूрди, рдХंрдкрдиीрдЪे рдиेрддृрдд्рд╡рд╣ी рддेрдЪ рдХрд░рдд рдЖрд╣ेрдд

 

рд╡िрдХ्рд░рдо-1 : рднाрд░рддीрдп рдЦाрдЬрдЧी рдЕंрддрд░ाрд│ рдХ्рд╖ेрдд्рд░ाрдЪा рдРрддिрд╣ाрд╕िрдХ рдЯрдк्рдкा

рд╣ैрджрд░ाрдмाрджрд╕्рдеिрдд рд╕्рдХाрдпрд░ूрдЯ рдПрд░ोрд╕्рдкेрд╕ рдпा 2018 рдордз्рдпे рд╕्рдеाрдкрди рдЭाрд▓ेрд▓्рдпा рд╕्рдЯाрд░्рдЯрдЕрдкрдиे рд╡िрдХрд╕िрдд рдХेрд▓ेрд▓्рдпा рд╡िрдХ्рд░рдо-1 рд░ॉрдХेрдЯрдЪ्рдпा рдпрд╢рд╕्рд╡ी рдк्рд░рдХ्рд╖ेрдкрдгाрдиे рднाрд░рддीрдп рдЕंрддрд░ाрд│ рдХ्рд╖ेрдд्рд░ाрдд рдирд╡े рдкрд░्рд╡ рд╕ुрд░ू рдЭाрд▓े рдЖрд╣े. рд╡िрд╢ेрд╖ рдо्рд╣рдгрдЬे рдпा рдк्рд░рдХрд▓्рдкाрдоाрдЧीрд▓ рд╡ैрдЬ्рдЮाрдиिрдХांрдЪी рд╕рд░ाрд╕рд░ी рд╡рдпोрдорд░्рдпाрджा 20 рддे 25 рд╡рд░्рд╖े рдЗрддрдХी рд╣ोрддी. рдпाрдоुрд│े рднाрд░рддाрддीрд▓ рдирд╡्рдпा рдкिрдвीрдЪी рд╡ैрдЬ्рдЮाрдиिрдХ рдХ्рд╖рдорддा рдЖрдгि рдирд╡ोрди्рдоेрд╖ाрдЪी рддाрдХрдж рдЕрдзोрд░ेрдЦिрдд рдЭाрд▓ी.

рдЖрдЬ рднाрд░рддाрдд рд╕ुрдоाрд░े 400 рд╣ूрди рдЕрдзिрдХ рд╕्рдЯाрд░्рдЯрдЕрдк्рд╕ рдЕंрддрд░ाрд│ рддंрдд्рд░рдЬ्рдЮाрди рдХ्рд╖ेрдд्рд░ाрдд рдХाрд░्рдпрд░рдд рдЖрд╣ेрдд. рдпाрдоुрд│े рдЗрд╕्рд░ोрдЪ्рдпा рдкрд▓ीрдХрдбे рдПрдХ рд╡्рдпाрдкрдХ рдЕंрддрд░ाрд│ рдЙрдж्рдпोрдЧ рдкрд░िрд╕ंрд╕्рдеा (Space Ecosystem) рд╡िрдХрд╕िрдд рд╣ोрдд рдЕрд╕рд▓्рдпाрдЪे рд╕्рдкрд╖्рдЯ рд╣ोрддे.

 

рдЕंрддрд░ाрд│ рддंрдд्рд░рдЬ्рдЮाрди : рднрд╡िрд╖्рдпाрддीрд▓ рдоूрд▓рднूрдд рдкाрдпाрднूрдд рд╕ुрд╡िрдзा

рдЪрд░्рдЪेрдд рдЕрд╕ा рдоुрдж्рджा рдоांрдбрдг्рдпाрдд рдЖрд▓ा рдХी, рдЬрд╕े рдЖрдЬ рдЗंрдЯрд░рдиेрдЯ рдЖрдкрд▓्рдпा рджैрдиंрджिрди рдЬीрд╡рдиाрдЪा рдЕрд╡िрднाрдЬ्рдп рднाрдЧ рдмрдирд▓े рдЖрд╣े, рддрд╕ेрдЪ рдЖрдЧाрдоी рдХाрд│ाрдд рдЕंрддрд░ाрд│ рддंрдд्рд░рдЬ्рдЮाрдирд╣ी рдоूрд▓рднूрдд рдЧрд░рдЬ рдард░рдгाрд░ рдЖрд╣े.

рд╣рд╡ाрдоाрди рдЕंрджाрдЬ, рдХृрд╖ी рдиिрдпोрдЬрди, рд╕ंрд░рдХ्рд╖рдг, рд╢िрдХ्рд╖рдг, рджूрд░рд╕ंрдЪाрд░, рдЖрдкрдд्рддी рд╡्рдпрд╡рд╕्рдеाрдкрди рдЖрдгि рдиेрд╡्рд╣िрдЧेрд╢рди рдпांрд╕ाрд░рдЦ्рдпा рд╕рд░्рд╡ рдХ्рд╖ेрдд्рд░ांрдЪा рдкाрдпा рдЙрдкрдЧ्рд░рд╣ рддंрдд्рд░рдЬ्рдЮाрдиाрд╡рд░ рдЖрдзाрд░िрдд рдЖрд╣े. рдд्рдпाрдоुрд│े рдЕंрддрд░ाрд│ рд╕ंрд╢ोрдзрди рд╣ा рдХेрд╡рд│ рдк्рд░рддिрд╖्рдаेрдЪा рд╡िрд╖рдп рдирд╕ूрди рд░ाрд╖्рдЯ्рд░ीрдп рд╡िрдХाрд╕ाрдЪा рдЖрдзाрд░рд╕्рддंрдн рдЖрд╣े.

 

рдЗрд╕्рд░ोрддीрд▓ 120 рд╡ैрдЬ्рдЮाрдиिрдХांрдЪे рдиिрд░्рдЧрдорди : рд╕ंрдХрдЯ рдХी рд╕्рд╡ाрднाрд╡िрдХ рдк्рд░рдХ्рд░िрдпा?

рдЗрд╕्рд░ोрдордзूрди 120 рд╡ैрдЬ्рдЮाрдиिрдХ рдмाрд╣ेрд░ рдкрдбрд▓्рдпाрдЪी рдмाрддрдоी рдоोрда्рдпा рдк्рд░рдоाрдгाрд╡рд░ рдЪрд░्рдЪेрдд рдЖрд▓ी. рддрдеाрдкि, рдпाрдХрдбे рдлрдХ्рдд рд╕ंрдХрдЯ рдо्рд╣рдгूрди рдкाрд╣рдг्рдпाрдРрд╡рдЬी рдЙрдж्рдпोрдЧ рдХ्рд╖ेрдд्рд░ाрддीрд▓ рдиैрд╕рд░्рдЧिрдХ рдк्рд░рдХ्рд░िрдпा рдо्рд╣рдгूрдирд╣ी рдкाрд╣рдгे рдЖрд╡рд╢्рдпрдХ рдЖрд╣े.

рдЦाрдЬрдЧी рдХ्рд╖ेрдд्рд░ाрдд рдЕрдзिрдХ рд╡ेрддрди, рдЪांрдЧрд▓्рдпा рд╕ंрд╢ोрдзрди рд╕ुрд╡िрдзा, рдЬрд▓рдж рдиिрд░्рдгрдп рдк्рд░рдХ्рд░िрдпा рдЖрдгि рдЕрдзिрдХ рд╕ंрдзी рдЙрдкрд▓рдм्рдз рдЕрд╕рд▓्рдпाрдоुрд│े рдЕрдиेрдХ рд╡ैрдЬ्рдЮाрдиिрдХांрдиी рдЦाрдЬрдЧी рдХंрдкрди्рдпांрдЪा рдоाрд░्рдЧ рд╕्рд╡ीрдХाрд░рд▓ा. рдЬрдЧрднрд░ाрддीрд▓ рддंрдд्рд░рдЬ्рдЮाрди рдЖрдгि рд╕ंрд╢ोрдзрди рдХ्рд╖ेрдд्рд░ाрдд рдЕрд╢ा рдк्рд░рдХाрд░рдЪे "Talent Migration" рд╕ाрдоाрди्рдп рдоाрдирд▓े рдЬाрддे.

рдпाрдоुрд│े рдХाрд╣ी рдк्рд░рдХрд▓्рдкांрдиा рддाрдд्рдкुрд░рддा рд╡िрд▓ंрдм рд╣ोрдК рд╢рдХрддो, рдкрд░ंрддु рд╣ी рдШрдЯрдиा рд╕ंрдкूрд░्рдг рдЕंрддрд░ाрд│ рдХाрд░्рдпрдХ्рд░рдоाрд╕ाрдаी рдШाрддрдХ рдЖрд╣े рдЕрд╕े рдоाрдирдг्рдпाрдЪे рдХाрд░рдг рдиाрд╣ी.

 

рдЬाрдЧрддिрдХ рд╕्рдкрд░्рдзेрдд рднाрд░рддाрдЪी рд╕्рдеिрддी

рднाрд░рдд рджрд░рд╡рд░्рд╖ी рд╕ुрдоाрд░े 13 рдк्рд░рдХ्рд╖ेрдкрдгे рдХрд░рдг्рдпाрдЪे рдЙрдж्рджिрд╖्рдЯ рдаेрд╡рдд рдЖрд╣े. рдпाрдЙрд▓рдЯ:

  • рдЪीрди рджрд░рд╡рд░्рд╖ी рд╕ुрдоाрд░े 100 рдк्рд░рдХ्рд╖ेрдкрдгे рдХрд░рддो.
  • рдЕрдоेрд░िрдХा рджрд░рд╡рд░्рд╖ी 200 рдкेрдХ्рд╖ा рдЕрдзिрдХ рдк्рд░рдХ्рд╖ेрдкрдгे рдХрд░рддे.

рднाрд░рдд рдЬрдЧाрддीрд▓ рдЪौрдеी рд╕рд░्рд╡ाрдд рдоोрдаी рдЕрд░्рдерд╡्рдпрд╡рд╕्рдеा рдмрдирдд рдЕрд╕рддाрдиा рдЕंрддрд░ाрд│ рд╕ंрд╢ोрдзрдиाрддीрд▓ рдЧुंрддрд╡рдгूрдХ рдЖрдгि рдк्рд░рдХ्рд╖ेрдкрдг рдХ्рд╖рдорддा рдпाрдордз्рдпेрд╣ी рддिрддрдХीрдЪ рд╡ाрдв рдЕрдкेрдХ्рд╖िрдд рдЖрд╣े.

 

рдЕрдоेрд░िрдХेрдЪे рдпрд╢ рдЖрдгि рдЦाрдЬрдЧी рдХ्рд╖ेрдд्рд░ाрдЪी рднूрдоिрдХा

рдЕрдоेрд░िрдХेрдЪ्рдпा рдпрд╢ाрдоाрдЧे рдХेрд╡рд│ рдиाрд╕ा рдирд╕ूрди SpaceX, Blue Origin, Rocket Lab рдпांрд╕ाрд░рдЦ्рдпा рдЦाрдЬрдЧी рдХंрдкрди्рдпांрдЪी рдорд╣рдд्рдд्рд╡рдкूрд░्рдг рднूрдоिрдХा рдЖрд╣े. рднाрд░рддाрддрд╣ी рд╕्рдХाрдпрд░ूрдЯ, рдЕрдЧ्рдиिрдХुрд▓, рдкिрдХ्рд╕ेрд▓, рдз्рд░ुрд╡ рд╕्рдкेрд╕, рдЧॅрд▓ेрдХ्рд╕рдЖрдп рдпांрд╕ाрд░рдЦ्рдпा рдХंрдкрди्рдпा рдЙрджрдпाрд╕ рдпेрдд рдЖрд╣ेрдд.

рдпाрдоुрд│े рдЗрд╕्рд░ोрдЪी рднूрдоिрдХा рдЖрддा "рдПрдХрдоेрд╡ рдЕंрддрд░ाрд│ рд╕ंрд╕्рдеा" рдЕрд╢ी рди рд░ाрд╣рддा "рдоाрд░्рдЧрджрд░्рд╢рдХ рдЖрдгि рдиिрдпाрдордХ рд╕ंрд╕्рдеा" рдЕрд╢ी рд╣ोрдд рдЖрд╣े.

 

рд░िрдпुрдЬेрдмрд▓ рд░ॉрдХेрдЯ्рд╕ рдЖрдгि рдШрдЯрдгाрд░ा рдЦрд░्рдЪ

рд░िрдпुрдЬेрдмрд▓ рд░ॉрдХेрдЯ्рд╕рдоुрд│े рдЙрдкрдЧ्рд░рд╣ рдк्рд░рдХ्рд╖ेрдкрдгाрдЪा рдЦрд░्рдЪ рдЭрдкाрдЯ्рдпाрдиे рдХрдоी рд╣ोрдд рдЖрд╣े.

  • рдХाрд╣ी рд╡рд░्рд╖ांрдкूрд░्рд╡ी 1 рдХिрд▓ो рдЙрдкрдЧ्рд░рд╣ рдХрдХ्рд╖ेрдд рдкाрдард╡िрдг्рдпाрдЪा рдЦрд░्рдЪ рд╕ुрдоाрд░े 55,000 рдбॉрд▓рд░ рд╣ोрддा.
  • рддो рдЖрдЬ рд╣рдЬाрд░ो рдбॉрд▓рд░рдкрд░्рдпंрдд рдЦाрд▓ी рдЖрд▓ा рдЖрд╣े.
  • рдкुрдвीрд▓ рджрд╢рдХाрдд рддो 100 рдбॉрд▓рд░ рдк्рд░рддि рдХिрд▓ोрдкेрдХ्рд╖ाрд╣ी рдХрдоी рд╣ोрдК рд╢рдХрддो.

рдпाрдоुрд│े рдЕंрддрд░ाрд│ рдХ्рд╖ेрдд्рд░ाрдЪे рд╡्рдпाрдкाрд░ीрдХрд░рдг (Commercialisation) рдоोрда्рдпा рдк्рд░рдоाрдгाрд╡рд░ рд╡ाрдврдг्рдпाрдЪी рд╢рдХ्рдпрддा рдЖрд╣े.

 

рдЗрд╕्рд░ोрд╕рдоोрд░ीрд▓ рдк्рд░рдоुрдЦ рдЖрд╡्рд╣ाрдиे

1. рдк्рд░рддिрднाрд╡ाрди рдордиुрд╖्рдпрдмрд│ рдЯिрдХрд╡рдгे

рдЗрд╕्рд░ोрд▓ा рдЖрддा рдЬाрдЧрддिрдХ рджрд░्рдЬाрдЪ्рдпा рдЦाрдЬрдЧी рдХंрдкрди्рдпांрд╢ी рд╕्рдкрд░्рдзा рдХрд░ाрд╡ी рд▓ाрдЧрдд рдЖрд╣े. рдд्рдпाрдоुрд│े рд╡ेрддрди, рд╕ंрд╢ोрдзрди рд╕ुрд╡िрдзा рдЖрдгि рдХрд░िрдЕрд░ рд╕ंрдзी рд╕ुрдзाрд░рдг्рдпाрдЪी рдЧрд░рдЬ рдЖрд╣े.

2. рд▓ाрд▓рдлिрддीрд╢ाрд╣ी

рд╡ैрдЬ्рдЮाрдиिрдХ рдиिрд░्рдгрдп рдк्рд░рдХ्рд░िрдпेрдд рдЕрдиाрд╡рд╢्рдпрдХ рдк्рд░рд╢ाрд╕рдХीрдп рд╣рд╕्рддрдХ्рд╖ेрдк рдХрдоी рдХрд░рдгे рдЖрд╡рд╢्рдпрдХ рдЖрд╣े. рдЕрдиेрдХ рд╡ेрд│ा рд╕ंрд╢ोрдзрди рдк्рд░рдХрд▓्рдк рдоंрдЬुрд░ीрдЪ्рдпा рдк्рд░рдХ्рд░िрдпेрддрдЪ рдЕрдбрдХрддाрдд.

3. рд╕рдХ्рд╕ेрд╢рди рдк्рд▓ॅрдиिंрдЧрдЪा рдЕрднाрд╡

рдорд╣рдд्рдд्рд╡ाрдЪ्рдпा рдкрджांрд╡рд░ рдХाрдо рдХрд░рдгाрд▒्рдпा рд╡ैрдЬ्рдЮाрдиिрдХांрдЪ्рдпा рдЬाрдЧी рдкрд░्рдпाрдпी рдордиुрд╖्рдпрдмрд│ рддрдпाрд░ рдаेрд╡рдг्рдпाрдЪी рдЖрд╡рд╢्рдпрдХрддा рдЖрд╣े.

4. рд╕ंрд╢ोрдзрдиाрд╡рд░ीрд▓ рдЕрдкुрд░ी рдЧुंрддрд╡рдгूрдХ

рднाрд░рддाрдЪे рдЕंрддрд░ाрд│ рд╕ंрд╢ोрдзрди рдмрдЬेрдЯ рд╕ुрдоाрд░े 1.6 рдЕрдм्рдЬ рдбॉрд▓рд░ рдЖрд╣े. рддुрд▓рдиा рдХрд░рддा:

  • рдЪीрди : рд╕ुрдоाрд░े 20 рдЕрдм्рдЬ рдбॉрд▓рд░
  • рдЕрдоेрд░िрдХा : 25 рдЕрдм्рдЬ рдбॉрд▓рд░рдкेрдХ्рд╖ा рдЕрдзिрдХ

 

рд╡ैрдЬ्рдЮाрдиिрдХ рд╕ंрд╕्рдХृрддी рд╡िрдХрд╕िрдд рдХрд░рдг्рдпाрдЪी рдЧрд░рдЬ

рднाрд░рддाрдд рд╡ैрдЬ्рдЮाрдиिрдХांрдЪ्рдпा рдХाрд░्рдпाрд▓ा рдЕрдкेрдХ्рд╖िрдд рд╕ाрдоाрдЬिрдХ рдоाрди्рдпрддा рдоिрд│рдд рдиाрд╣ी. рдХ्рд░िрдХेрдЯрдкрдЯू рдХिंрд╡ा рдЪिрдд्рд░рдкрдЯ рдХрд▓ाрдХाрд░ांрдЪ्рдпा рддुрд▓рдиेрдд рд╢ाрд╕्рдд्рд░рдЬ्рдЮांрдиा рд╕рдоाрдЬाрдд рдХрдоी рдк्рд░рд╕िрдж्рдзी рдоिрд│рддे.

рд╡िрдХ्рд░рдо-1 рд╕ाрд░рдЦ्рдпा рдпрд╢рд╕्рд╡ी рдоोрд╣िрдоांрдмрдж्рджрд▓ рд╢ाрд│ा рдЖрдгि рдорд╣ाрд╡िрдж्рдпाрд▓рдпांрдордз्рдпे рдЪрд░्рдЪा рд╡्рд╣ाрд╡ी, рд╡िрдж्рдпाрд░्рде्рдпांрдордз्рдпे рд╡िрдЬ्рдЮाрдиाрдмрдж्рджрд▓ рдЖрдХрд░्рд╖рдг рдиिрд░्рдоाрдг рд╡्рд╣ाрд╡े рдЖрдгि рд╡ैрдЬ्рдЮाрдиिрдХ рдпрд╢ाрдЪे рд╕ाрд░्рд╡рдЬрдиिрдХ рд╕ाрдЬрд░ीрдХрд░рдг рд╡्рд╣ाрд╡े, рдЕрд╢ी рдЧрд░рдЬ рд╡्рдпрдХ्рдд рдХрд░рдг्рдпाрдд рдЖрд▓ी.

 

рднрд╡िрд╖्рдпाрддीрд▓ рдЕंрддрд░ाрд│ рдЕрд░्рдерд╡्рдпрд╡рд╕्рдеा

рддрдЬ्рдЬ्рдЮांрдЪ्рдпा рдорддे, рдкुрдвीрд▓ рджрд╢рдХाрдд:

  • рдЕंрддрд░ाрд│ рдкрд░्рдпрдЯрди (Space Tourism)
  • рдЕрд╡рдХाрд╢ाрддीрд▓ рдЙрдд्рдкाрджрди (Space Manufacturing)
  • рдФрд╖рдзрдиिрд░्рдоिрддी рд╕ंрд╢ोрдзрди
  • рдЙрдкрдЧ्рд░рд╣ рдЗंрдЯрд░рдиेрдЯ рд╕ेрд╡ा
  • рдЪंрдж्рд░ рдЖрдгि рдоंрдЧрд│ाрд╢ी рд╕ंрдмंрдзिрдд рдЙрдж्рдпोрдЧ

рдпाрдордз्рдпे рдоोрда्рдпा рдк्рд░рдоाрдгाрд╡рд░ рд╡ाрдв рд╣ोрдгाрд░ рдЖрд╣े.

рд╕्рдкेрд╕ рдЖрдгि рдЗंрдЯрд░рдиेрдЯ рддंрдд्рд░рдЬ्рдЮाрди рдпांрдЪा рд╕ंрдЧрдо рднрд╡िрд╖्рдпाрддीрд▓ рдирд╡्рдпा рдЕрд░्рдерд╡्рдпрд╡рд╕्рдеेрдЪा рдкाрдпा рдард░ेрд▓.

 

рднाрд░рддाрд╕ाрдаी рдкुрдвीрд▓ рдоाрд░्рдЧ

рднाрд░рддीрдп рдЕंрддрд░ाрд│ рдХ्рд╖ेрдд्рд░ाрдЪ्рдпा рд╡ेрдЧрд╡ाрди рд╡िрдХाрд╕ाрд╕ाрдаी рдЦाрд▓ीрд▓ рдЙрдкाрдп рдЖрд╡рд╢्рдпрдХ рдЖрд╣ेрдд:

  1. рдЕंрддрд░ाрд│ рд╕ंрд╢ोрдзрдиाрд╕ाрдаी рдоोрда्рдпा рдк्рд░рдоाрдгाрд╡рд░ рдиिрдзी рд╡ाрдврд╡рдгे.
  2. рд╡ैрдЬ्рдЮाрдиिрдХांрдЪे рд╡ेрддрди рдЖрдгि рд╕ुрд╡िрдзा рд╕ुрдзाрд░рдгा.
  3. рдиिрд░्рдгрдп рдк्рд░рдХ्рд░िрдпेрдд рд▓ाрд▓рдлिрддीрд╢ाрд╣ी рдХрдоी рдХрд░рдгे.
  4. рдЦाрдЬрдЧी рдХ्рд╖ेрдд्рд░ाрд▓ा рдЕрдзिрдХ рдк्рд░ोрдд्рд╕ाрд╣рди рджेрдгे.
  5. рд╡िрдЬ्рдЮाрди рд╢िрдХ्рд╖рдгाрдЪा рдк्рд░рд╕ाрд░ рдХрд░рдгे.
  6. рд╕ंрд╢ोрдзрди рдЖрдгि рдирд╡ोрди्рдоेрд╖ рд╕ंрд╕्рдХृрддी рдмрд│рдХрдЯ рдХрд░рдгे.
  7. рд░ाрд╖्рдЯ्рд░ीрдп рд╕्рддрд░ाрд╡рд░ рд╡ैрдЬ्рдЮाрдиिрдХांрдЪा рдЧौрд░рд╡ рд╡ाрдврд╡рдгे.

 

рдиिрд╖्рдХрд░्рд╖

рд╡िрдХ्рд░рдо-1 рдЪे рдпрд╢ рд╣े рдХेрд╡рд│ рдПрдХा рд╕्рдЯाрд░्рдЯрдЕрдкрдЪे рдпрд╢ рдирд╕ूрди рднाрд░рддीрдп рдЕंрддрд░ाрд│ рдХ्рд╖ेрдд्рд░ाрдЪ्рдпा рдирд╡्рдпा рдпुрдЧाрдЪी рд╕ुрд░ुрд╡ाрдд рдЖрд╣े. рдЗрд╕्рд░ोрдордзीрд▓ рдХाрд╣ी рд╡ैрдЬ्рдЮाрдиिрдХांрдЪे рдиिрд░्рдЧрдорди рд╣ी рдЪिंрддेрдЪी рдмाрдм рдЕрд╕рд▓ी рддрд░ी рддी рд╡ाрдврдд्рдпा рд╕्рдкрд░्рдзेрдЪे рдЖрдгि рд╡िрд╕्рддाрд░рдд рдЪाрд▓рд▓ेрд▓्рдпा рдЕंрддрд░ाрд│ рдЙрдж्рдпोрдЧाрдЪे рд▓рдХ्рд╖рдг рдЖрд╣े.

рднाрд░рддाрдЪे рднрд╡िрд╖्рдп рдХेрд╡рд│ рдЗрд╕्рд░ोрдЪ्рдпा рдЦांрдж्рдпाрд╡рд░ рдЕрд╡рд▓ंрдмूрди рд░ाрд╣рдгाрд░ рдиाрд╣ी. рдЗрд╕्рд░ो, рдЦाрдЬрдЧी рдЙрдж्рдпोрдЧ, рд╕्рдЯाрд░्рдЯрдЕрдк्рд╕, рд╕ंрд╢ोрдзрди рд╕ंрд╕्рдеा рдЖрдгि рддрд░ुрдг рд╡ैрдЬ्рдЮाрдиिрдХ рдпांрдЪे рдПрдХрдд्рд░िрдд рдк्рд░рдпрдд्рди рднाрд░рддाрд▓ा рдЬाрдЧрддिрдХ рдЕंрддрд░ाрд│ рдорд╣ाрд╕рдд्рддा рдмрдирд╡ू рд╢рдХрддाрдд. рд╡िрдХ्рд░рдо-1 рдиे рдпा рджिрд╢ेрдиे рдкрд╣िрд▓े рдорд╣рдд्рдд्рд╡рдкूрд░्рдг рдкाрдКрд▓ рдЯाрдХрд▓े рдЕрд╕ूрди, рдЖрдЧाрдоी рджрд╢рдХ рднाрд░рддाрдЪ्рдпा рдЕंрддрд░ाрд│ рдк्рд░рд╡ाрд╕ाрд╕ाрдаी рдиिрд░्рдгाрдпрдХ рдард░рдгाрд░ рдЖрд╣े.