Why We Believe Universities Need a Favoriot Platform Ecosystem, Not Just IoT Accounts

I shared this idea in a recent product presentation, but the more I reflect on it, the more I feel this deserves to be written down properly. Slowly. Honestly. With feeling.

Because this is not just about plans and pricing.
This is about how we teach, how we learn, and how knowledge grows over time.

I remember pausing for a moment before the session began.
“Do people really see this problem yet?” I asked myself.

Most do not. And that is exactly why I want to tell this story.

The quiet problem nobody talks about

For years, I have watched how IoT is taught in universities.

Students are told, “Go subscribe.”
Lecturers say, “Use whatever tools you can find.”
Labs run on goodwill, workarounds, and personal accounts.

On the surface, it looks fine.

Free plans here.
A few paid plans there.
Some students pay out of pocket.
Some lecturers try to stretch limited lab budgets.

But beneath that surface, something feels broken.

I thought to myself, this is not how serious engineering should feel.

IoT is not a hobby once it enters a lab.
It is not a toy when it becomes a Final Year Project.
It is not casual when research data needs months, sometimes years, to mature.

Yet we treat the tooling like disposable apps.

Individual accounts versus institutional thinking

Most users experience Favoriot through individual plans. Free. Lite. Beginner. Developer.

That makes sense at the start.

You are curious.
You want to test.
You want to learn.

But universities are not individuals.

They are systems.

And systems need structure.

What usually happens today is this:

A student creates an account.
They collect data for a semester.
They graduate.
The account disappears.
The data disappears.
The knowledge disappears.

And every time this happens, I feel a quiet sense of loss.

Because data is not just numbers.
Data is effort.
Data is learning.
Data is time that never comes back.

The moment the question became clear

During the session, I asked a simple question.

What if universities could manage IoT accounts the way they manage labs?

What if, instead of hundreds of disconnected student subscriptions, there was one administrator, one place of control, one long-term memory?

That question changed everything.

I remember thinking, this is the missing layer.

What an IoT Ecosystem Plan really means

The Favoriot IoT Ecosystem Plan is not a fancy label.

It is a mindset shift.

Instead of students owning accounts, the institution owns the ecosystem.

One administrator manages a pool of plans.
Beginner. Lite. Developer.
Whatever fits the teaching or research need.

Accounts can be allocated.
Accounts can be rotated.
Accounts can be reused.

No chaos.
No loss.
No, starting from zero every semester.

A lab that finally makes sense

Imagine a lab with thirty Beginner plans.

The admin assigns ten accounts for this semester’s lab class.
Students log in.
They build.
They experiment.
They learn.

Next semester, the same accounts are reused by a new cohort.

I smiled when I explained this part.
Because this is how labs should work.

Not emotional budgeting.
Not last-minute subscriptions.
Not students asking, “Sir, do I really need to pay for this?”

Final Year Projects without financial anxiety

Final Year Projects are intense.

Students are already under pressure.
Deadlines.
Expectations.
Demonstrations.

Now add one more burden: the cost of tools.

I paused again when I talked about this.
“Why are we doing this to them?” I wondered.

Under the ecosystem plan, the department allocates accounts to FYP students.

No personal subscriptions.
No awkward reimbursements.
No half-built systems because the plan expired.

Just focus.
Just building.
Just learning.

Research data that does not vanish

This part matters deeply to me.

Research does not run on semesters.

Some datasets need months.
Some need a full year.
Some become valuable only after long observation.

In individual accounts, when a researcher leaves, the data often goes with them.

With an ecosystem plan, the data stays.

The account belongs to the institution.
The history remains intact.
The next researcher continues the story.

I remember thinking, this is how real research continuity should feel.

One dashboard. One view. One sense of control

Administrators often feel blind.

Who is using what?
Who is stuck?
Which lab is active?
Which accounts are idle?

An integrated dashboard changes that.

You can see progress.
You can spot gaps.
You can improve training.

This is not about surveillance.
This is about care.

Care for students.
Care for lecturers.
Care for outcomes.

Not one-size-fits-all, and that is the point

Some universities need thirty Beginner plans.
Some need seventy.
Some mix Beginner with Developer plans.

That is why ecosystem plans are quoted, not clicked.

Because education does not fit into neat boxes.

I told myself, flexibility is respect.

Respect for different teaching styles.
Respect for different research scales.
Respect for different budgets.

Why I feel strongly about this

I have spent decades in education, industry, and startups.

I have seen what happens when systems are built for convenience instead of continuity.

And I have also seen what happens when institutions think long-term.

This ecosystem idea is not about selling more plans.
It is about lifting the quality of learning.

It is about treating IoT education as a serious craft.

A quiet invitation

If you are a lecturer, ask yourself this:

Are your students building knowledge, or just finishing assignments?

If you are a researcher, ask this:

Will your data still matter when you move on?

If you are an administrator, ask this:

Is your IoT lab a collection of accounts, or a living system?

I know my answer.

I believe universities deserve an IoT ecosystem that grows with them, remembers with them, and supports the next generation better than we were supported.

If this idea resonates with you, I would love to hear your thoughts.

Drop a comment.
Challenge it.
Improve it.

That is how ecosystems begin.

ChatGPT, CoPilot, Gemini, Grok, Perplexity, Claude & DeepSeek: Which One Should You Choose?

Here’s a breakdown of the main features to help you decide which AI tool suits your needs:

1️⃣ ChatGPT (OpenAI)

✅ Versatile and reliable: Perfect for writing tasks, explaining technical concepts, and generating or debugging code.

✅ Supports multiple languages: Works well even in non-English languages, including Malay.

✅ Developer-friendly: Offers a stable API, making it ideal for building applications with AI capabilities.

❌ Paid plans for heavy use: A subscription is required to unlock more advanced features or handle large-scale tasks.

2️⃣ Gemini (Google, formerly Bard)

✅ Live search integration: It’s directly connected to Google Search, making it great for delivering the most up-to-date information.

✅ Fact-focused: Excels at answering general knowledge questions and providing factual details.

❌ Context sensitivity can be inconsistent: Sometimes, struggles to grasp complex or nuanced questions fully.

3️⃣ CoPilot (Microsoft, powered by GPT-4 Turbo)

✅ Productivity-focused: Fully integrated with Microsoft Office tools like Word and Excel, making it a powerful assistant for work-related tasks.

✅ Seamless Windows integration: An excellent choice for Windows users who need AI within their workflow.

❌ Access requirements: You’ll need a Microsoft account; in some cases, access may be restricted to specific users or organisations.

4️⃣ Grok (X, by Elon Musk)

✅ Social media-savvy: Specially designed for users of X (formerly Twitter), offering features to analyse and follow social media trends.

✅ Trend-aware: Focuses on staying current with the latest online conversations.

❌ Still evolving: As a relatively new tool, it lacks the maturity and extensive testing of more established platforms.

5️⃣ DeepSeek AI

✅ Specialist in technical fields: Excellent for research, coding, and solving complex mathematical problems.

✅ Completely free: A budget-friendly option for students, researchers, or anyone exploring technical AI applications.

❌ Limited advanced features: Compared to tools like ChatGPT or Gemini, it doesn’t offer comprehensive capabilities or integrations yet.

6️⃣ Perplexity AI

✅ Great for fact-checking: It can reference the internet in real-time, making it highly effective for quick research or verifying information.

✅ Focused research tool: Handy for researching specific topics and finding credible sources.

❌ Can lack deeper understanding: Tends to compile data rather than analyse or interpret it meaningfully.

7️⃣ Claude (Anthropic)

✅ Contextually intelligent: Known for its ability to generate high-quality text and clearly understand the context in conversations.

✅ Safe and ethical: Less prone to producing harmful, biased, or inaccurate content, making it a reliable option.

❌ Less recognition locally: Not as widely known or used in Malaysia, though its features are robust and competitive.

How to Choose the Right AI for Your Needs

  •  For writing, coding, or creative projects, → Go for ChatGPT or Claude for their depth and versatility.
  •  If you need real-time information or up-to-date research, → Consider Gemini or Perplexity.
  •  To boost productivity at work with office tools, → Use CoPilot, which works seamlessly with Microsoft applications.
  •  Social media enthusiasts → Try Grok, designed to help navigate trends on X (Twitter).
  •  For technical problem-solving or coding on a budget, → Choose DeepSeek AI.

Each tool has unique strengths, so the choice depends on your specific use case and preferences.

Why Building AI and IoT Products Locally Can Save a Country

The appearance of DeepSeek, which shook the world, taught us an important lesson — technology sovereignty.

Have you ever wondered why some countries have more control over their technology and future? It’s not magic.

They’ve invested time and effort in developing their technologies, especially in Artificial Intelligence (AI) and the Internet of Things (IoT).

These two areas are no longer just fancy buzzwords – they are the backbone of modern nations.

Let me explain why building these technologies locally is essential and could be a real game-changer for any country.

Keeping Our Data Safe

Think about how much data is collected daily – from your smartwatches, smartphones, traffic cameras, and building sensors. All of this data tells a story about us, about our country.

If this data goes to foreign companies, they control it, not us. That’s scary, right?

When we build AI and IoT products locally, we keep our data within our borders. We don’t have to rely on someone else to store or protect it.

This means we reduce the chances of our information falling into the wrong hands. It’s like having your valuables locked in your safe rather than someone else’s.

Protecting Our Security

Imagine if someone could hack into your country’s power grid or water supply.

What happens then? Chaos.

That’s why it’s essential to have secure technologies. When we depend on foreign-made systems, we give our critical infrastructure to them.

Local AI and IoT solutions can protect public transportation, hospitals, and defence systems. It’s like building a strong fortress – we control who gets in and out.

Creating Jobs and Boosting the Economy

Here’s the fun part – when we make our own AI and IoT products, we create jobs.

Think about all the engineers, researchers, factory workers, and even marketers involved in these projects.

Big companies like Google invest billions in countries like Malaysia to help build these technologies locally.

Google’s recent investment is expected to create over 26,000 jobs in Malaysia alone. Imagine what we can do if we take the lead ourselves!

Making Technology That Fits Us

Sometimes imported technology doesn’t work well for us because it wasn’t designed with our needs in mind.

For example, an IoT system designed for a cold country might not work perfectly in Malaysia’s tropical climate, or an AI chatbot might not understand our local languages or culture.

When we create our products, we can ensure they are right for us. We can design innovative farming tools for our crops, smart city systems for our traffic, and AI systems that understand Malay and other local languages.

Staying Strong During Global Tensions

Let’s be honest – the world is full of political tensions. Trade wars and sanctions can disrupt access to foreign technologies. I

f we rely too much on others, what happens when they suddenly pull the plug?

By building our own AI and IoT, we ensure that our systems continue running no matter what happens in the rest of the world. It’s like growing your food instead of relying on someone else’s farm.

Saving Money in the Long Run

When we use foreign technologies, we often have to pay licensing fees or deal with high costs.

Local solutions cut out the middleman, making things cheaper for businesses and citizens.

Plus, the money stays in the country, helping our economy grow further.

Empowering Our People

One of the most inspiring parts of building local technologies is how they empower our people. It gives our youth opportunities to work on cutting-edge projects without having to leave the country.

It also encourages entrepreneurship, where anyone with a good idea can start their own business.

We’ve seen how tech-savvy countries like China and India are building their systems and becoming global leaders.

Why can’t we do the same? We have the talent; we need the vision and support.

Keeping Control Over Our Culture

AI and IoT shape how we live, work, and even think. If these technologies come from other countries, they might not reflect our values and culture.

Building our systems means ensuring they align with what’s important to us as a nation.

For example, we can develop AI systems that promote our local heritage, preserve our languages, and respect our cultural norms.

It’s about staying true to who we are while moving forward.

A Future We Control

Building AI and IoT products locally is about one thing – control. It’s about taking charge of our future rather than leaving it in someone else’s hands. It’s about ensuring that our technology serves us and not vice versa.

Countries like Malaysia are already taking steps in this direction with investments in AI parks and national AI offices. But this is just the beginning. With the right mindset, resources, and determination, we can become leaders in this space.

So, the next time someone asks why local AI and IoT matter, remember – it’s not just about technology.

It’s about independence, security, and building a future we can be proud of.

The Story Behind Favoriot – Part 3: Why No One Wanted Our IoT Platform—And How We Turned It Around

The Beginning of a Daunting Journey

In 2019, we officially launched our self-developed IoT services with high hopes. The FAVORIOT IoT platform was our pride and joy—a product we believed could transform how data is collected, processed, and visualized. Yet, reality hit us hard. No one wanted to use it.

I still remember the sting of those early days. We offered our platform for free to the first ten customers to gain traction, but even that didn’t work. “Why doesn’t anyone want to use our platform?” I would ask myself almost every night.

It wasn’t just a passing thought but an all-consuming question that kept me awake. Was our product flawed? Did we miss something crucial?

The truth was more complicated to accept than I imagined. The issue wasn’t with our product’s functionality or potential—it was the lack of understanding about IoT itself. People didn’t know how to use an IoT platform because they didn’t know what IoT could do for them. This was not just a technical problem but a knowledge gap that needed bridging.

Planting Seeds of IoT Awareness in Universities

I’ve always believed that education is the foundation of progress. As an Industry Advisory Panel member at several universities, I saw an opportunity to address this knowledge gap. In meetings with lecturers and deans, I passionately advocated for curriculum changes.

We need to teach students how to use IoT technology more systematically,” I said repeatedly. “It’s not just about theory; it’s about hands-on experience.”

Slowly, my efforts began to bear fruit. Universities started incorporating IoT-focused courses into their programs, and students were introduced to connected devices. Knowing that a new generation of tech-savvy individuals was emerging was a proud moment for me.

But just when I thought the tides were turning, I encountered another challenge.

Why Not Favoriot?

Despite the growing interest in IoT, many students opted for platforms like Blynk and ThingSpeak for their final-year projects. It was disheartening to see them bypass Favoriot. I couldn’t help but wonder, “Why aren’t they choosing us? What does our platform lack compared to these alternatives?

It wasn’t just about competition—it was about understanding what made those platforms more appealing. I realized that we needed to work harder to showcase Favoriot’s value, unique features, and potential to become the preferred IoT platform for students and professionals.

Introducing Favoriot to the World

Determined to make a change, I began organizing seminars and workshops to introduce the Favoriot IoT Platform to the public. Each event allowed me to share my vision and educate participants about the platform’s capabilities.

I would stand in front of the audience, often a mix of students, lecturers, and industry professionals, and speak with passion:

This platform is not just for students. It’s for professionals and large companies, too. It’s designed to support larger R&D projects and commercial applications.”

The road wasn’t easy, but gradually, people started paying attention. They saw the potential in Favoriot—not just as another IoT platform but as a solution tailored to meet diverse needs.

The Turning Point

By 2024, our persistence began to pay off. Favoriot was no longer an unknown name in the IoT landscape. Out of 9,375 users (as of January 27, 2025), 80% came from our own country—a milestone that filled me with pride.

We did it,” I told my team with a sense of accomplishment. “We’ve proven that we can compete with global platforms and carve out our own space.

The Favoriot IoT Platform is now widely used for collecting data in larger R&D projects and commercial applications. It has become a trusted tool for those who see the power of IoT in solving real-world challenges.

Reflections and Looking Ahead

As I reflect on this journey, I can’t help but feel grateful for the challenges we faced. They taught us resilience, creativity, and the importance of education in driving technological adoption.

But our story doesn’t end here. Favoriot is still evolving, and we’re just scratching the surface of what’s possible. We aim to expand beyond Malaysia, reach users worldwide, and continue empowering individuals and organizations with IoT solutions.

This journey is a testament to the power of perseverance and the impact of believing in your vision. I say to anyone facing challenges in their entrepreneurial journey, don’t give up.

Every obstacle is an opportunity to learn, grow, and return stronger.

Stay tuned for the next chapter of our story, where I’ll share how Favoriot continues to innovate and expand its reach.

More Stories About Entrepreneurship

  1. The Story Behind Favoriot – Part 6: Expanding The Business Models
  2. The Story Behind Favoriot – Part 5: Finding the Right Fit
  3. The Story Behind Favoriot – Part 4: How Favoriot Became More Than Just an IoT Platform
  4. The Story Behind Favoriot – Part 3: Why No One Wanted Our IoT Platform—And How We Turned It Around
  5. The Story Behind Favoriot – Part 2: Turning Failures into Milestones
  6. The Story Behind Favoriot – Part I: The Humble Beginnings of Favoriot
  7. Building My Personal Brand: The Stepping Stone to Favoriot’s Success
  8. From Research Lab Critiques to Startup Pitches: My Slide Story
  9. The Illusion of RFPs in the IoT World: Managing Expectations as a Startup
  10. Favoriot’s Odyssey: Navigating the Rough Waters of Early Revenue