I’ve always been curious about what makes some articles perform better than others.
So, when I looked at my top earners, a few patterns jumped out at me.
Let me walk you through what I noticed.
1. Relevant and Practical Topics
The first article on the list, “Five (5) Best Reasons Why I Chose Gumroad to Sell My eBooks,” wasn’t surprising. It speaks directly to content creators like me who want to sell digital products. It’s straightforward, helpful, and, most importantly, actionable. That’s a formula that works.
Similarly, “Avoid These 10 Mistakes and Become a Better Writer in 2024” was a hit because, let’s face it, who doesn’t want to improve their writing?
Tackling common mistakes is something almost every writer can relate to.
That relatability gave it an edge.
2. Timing is Everything
I realised that timing plays a huge role. Articles like “Avoid These 10 Mistakes…” and “Lessons Learned Before and After Joining Medium Partner” were published around the start of the year.
That’s when people are most motivated to learn, grow, and try new things.
It’s like catching a wave at just the right moment.
3. Actionable Tips Win Hearts
I’ve learned that people love actionable advice — stuff they can use right away.
Writing about practical steps, like optimising writing habits or selling eBooks, clicks with readers.
They see immediate value in it. Articles like “Five (5) Best Reasons Why I Chose Gumroad” stand out because they’re not just informative but useful.
4. Engagement Makes a Difference
This part surprised me.
Some articles didn’t just get views — they got a lot of reads. For example, the Gumroad article had 184 reads out of 349 views.
That’s over 50%! It tells me the people who clicked on it stuck around to read the whole thing.
Compare that to other articles that might have more views but fewer reads — it’s clear which ones connected with people.
5. Storytelling Works Wonders
I’ve always loved weaving personal stories into my writing, and readers seem to enjoy that, too. “A Letter to My Younger Self” is a great example.
It’s reflective and emotional; I think people appreciate that human touch.
It’s not just another “how-to” article — it’s a glimpse into my journey.
6. Short and Sweet Wins
Looking at the data, I noticed the sweet spot for article length is around 3–5 minutes.
These are long enough to deliver value but short enough to fit into a busy reader’s day. Articles like “Avoid These 10 Mistakes…” and “Lessons Learned…” are perfect examples.
They pack a punch without dragging on.
7. Niche Matters
Some articles do well because they speak directly to a specific group.
Take “Lessons Learned Before and After Joining Medium Partner,” for instance. It’s aimed at Medium writers, who are probably searching for that content.
I think finding the right niche is half the battle.
8. Eye-Catching Titles
I’ll admit that titles matter more than I used to think. Something like “Tripling My Medium December Earnings: When I Implement These Amazing Things” immediately grabs attention.
Words like “tripling” and “amazing” spark curiosity, and curiosity gets clicks.
Looking back, it’s clear that the combination of timing, practical value, personal voice, and targeting the right audience made these articles stand out.
And while I can’t always predict which ones will resonate the most, seeing these patterns emerge is fascinating.
Writing is as much about experimenting as it is about connecting with readers; I’m always learning.
Below are the top 5 highest earned articles in 2024.
As I get ready to start my day, I think about something I often ask myself: “What exactly is an AI agent?” It’s not just another complicated tech term; it’s an idea changing how we use technology and go about our daily lives.
An AI agent is like a super-smart assistant that can understand its surroundings, make decisions, and take actions to meet specific goals— all without needing constant instructions.
But what does “understand its surroundings” actually mean?
Picture a world where IoT sensors are like the eyes and ears of an AI agent. These sensors are embedded everywhere: in your home, your car, factories, farms, and even in your city.
They collect real-time data about everything — temperature, motion, air quality, energy use, etc.
An AI agent processes this data to get a clear picture of what’s happening and decides what to do next.
For example, a smart thermostat uses temperature sensors to learn when to heat or cool your home based on your habits.
On a larger scale, in a smart city, IoT sensors on traffic lights help an AI agent manage traffic flow, reducing congestion during rush hour.
Why AI Agents Matter
Picture a day when your assistant reminds you about meetings, plans your route to avoid traffic, and even orders your favourite snacks when you’re running low.
It’s not just about making life easier; it’s about being smarter with your time and energy.
Here are some reasons why AI agents are so helpful:
Getting Things Done Faster: AI agents handle repetitive tasks like summarizing emails or making reports, leaving you free to focus on more significant ideas. Imagine never having to waste time on tedious chores again.
Making Life Personal: AI agents learn about you — what you like and need — and give you tailored suggestions. Whether finding a new show to watch or giving health advice, they make things feel just right for you.
Handling Big Loads: AI agents can manage a ton of work without slowing down in businesses. From answering customer questions to keeping track of supplies, they handle it all smoothly.
Getting Smarter Over Time: Unlike regular systems that don’t change, AI agents learn from every interaction and improve continuously. They adapt to new challenges and keep getting better at helping you.
As I think about these benefits, I wonder: “Why is 2025 the year for AI agents?” The answer lies in how technology advances, businesses are ready, and people are trusting AI more.
Why 2025 Will Be the Year for AI Agents
There are several reasons why 2025 is shaping up to be a big year for AI agents:
More Companies Using Them: Businesses realise how helpful AI agents can be. From helping customers to improving healthcare, these agents are becoming a must-have tool.
Better Technology: AI agents are more intelligent than ever, thanks to language understanding and decision-making improvements. They can now handle complex tasks and make real-time choices.
People Trust Them More: More and more people are comfortable using AI tools. For example, in 2024, the number of people using chatbots during the holiday shopping season skyrocketed — a clear sign that consumers are embracing AI.
Industry Innovation: New AI tools designed for specific tasks make it easier for businesses and individuals to adopt these technologies. For example, personal virtual assistants are now more competent and more accessible than ever.
“It’s not just about cool gadgets,” I remind myself. “It’s about creating a system that works for everyone.” That’s why things like data security and ethical AI are so important.
IoT and AI Agents: A Perfect Team
As someone who works closely with IoT (Internet of Things), I often think about how it fits with AI agents. IoT connects devices — like your smartwatch, fridge, or car — creating a network that collects loads of data.
But data alone isn’t valuable. AI agents are like the brain that makes sense of everything and acts on it.
Here’s how they work together:
Making Data Useful: IoT devices collect information, but AI agents turn it into insights you can use. For example, a smart home can learn your daily habits and automatically adjust the lights or temperature to save energy.
Deciding on Their Own: IoT sensors check the soil in agriculture, and AI agents choose when and how much to water crops. In healthcare, wearable devices monitor your health, and AI agents alert your doctor if something looks off.
Simple and Easy to Use: Instead of confusing dashboards, you can just ask your AI agent questions like, “How much energy did we save this month?” and get clear answers.
Managing Big Systems: Managing IoT networks can be a headache as they grow. AI agents make it simple by adapting to new devices and managing everything efficiently. In smart cities, they can control traffic lights to ease congestion.
Improving Shopping Experiences: IoT sensors track what’s on the shelves in stores, and AI agents reorder items before they run out. It’s all about making sure customers get what they need without waiting.
Helping the Environment: AI agents and IoT can reduce waste and save energy. Smart grids distribute electricity more efficiently, and AI agents optimize energy use at home and in factories.
“Imagine this,” I think, “Your car tells your home’s AI agent you’re on your way. The garage door opens, the lights turn on, and the air conditioning adjusts to your preferred temperature. That’s the future — where everything works together seamlessly.”
The Road Ahead
Of course, there are challenges. People worry about privacy and security. “How do we ensure AI agents work for us and not against us?” That’s a question I often come back to.
But the potential is enormous.
AI agents combined with IoT can change industries, simplify life, and solve problems in ways we’ve never seen before.
From improving healthcare to creating smarter cities, the possibilities are endless.
As I wrap up my thoughts, I feel excited about what’s to come. The year 2025 will be a turning point for AI agents and how we live and work.
It’s a year that could redefine everything.
So, let’s get ready to embrace this change. Let’s use AI agents to create a more imaginative, more connected world.
The future isn’t something we wait for — it’s something we build together.
When I started exploring the world of IoT, one of the first things I noticed was how fragmented the ecosystem seemed.
Every project required a different set of tools, and connecting the dots — devices, platforms, and data — felt like piecing together a jigsaw puzzle without knowing what the final picture would look like.
I didn’t want to create just another IoT platform; I tried to solve real problems that educators, students, and developers face daily.
Let me take you through it in my own words.
The Real Problem with IoT Education
During one of my visits to a university, I candidly chatted with an educator who shared their frustrations about their IoT lab.
“We have the hardware,” they said, pointing at a table full of Arduino boards and sensors. “But the students never get the complete picture. They build projects, but these projects live in isolation, never really demonstrating what IoT is capable of in the real world.” That conversation stayed with me.
I started asking others in the field; the story was the same everywhere. Students spend more time figuring out middleware and less time learning how IoT could transform industries.
And worse, most of their projects died after submission — no data continuity, no way to scale, and no means to manage the work if they wanted to revisit it later.
That’s when I realised we needed to bridge this gap.
Enter FAVORIOT: Built with Real Challenges in Mind
When we designed the FAVORIOT IoT Ecosystem, we didn’t start with features — we started with problems.
Could we make it effortless for students and developers to integrate their devices into an IoT platform? What if educators could easily create a complete IoT lab experience without assembling a dozen tools? These questions drove our design.
I remember thinking, “It’s not about cramming features into a platform; it’s about solving headaches.”
Take, for example, the issue of middleware. I’ve seen students spend weeks deciding which middleware to use, only to hit a wall regarding implementation.
FAVORIOT eliminates this by offering a ready-to-use IoT platform that handles device management, data ingestion, and visualisation — all in one place.
What Does This Mean for Educators and Students?
Let’s go back to that IoT lab I visited.
Imagine if those Arduino boards and sensors were connected to FAVORIOT. Suddenly, students wouldn’t just be building isolated projects; they’d be building scalable IoT solutions.
They’d learn how to send real-time data from their devices to the cloud, process and analyse it, and visualise it for meaningful insights. Isn’t that what IoT is all about?
And for educators, the value is clear. “How do I make IoT exciting for my students?” an instructor asked me. FAVORIOT gives them the tools to answer that question.
Providing a complete ecosystem lets them focus on teaching concepts rather than troubleshooting technical hurdles.
Students get hands-on experience with a real-world IoT platform, and educators see their students’ potential fully realised.
Solving the Continuity Problem
One of the most significant pain points I’ve heard is the lack of project continuity. Students build something impressive, present it, and then… it’s gone.
There’s no scalable database to store the data, no device management to maintain the system, and no way to build upon the project later. FAVORIOT changes that.
Features like data storage and device scalability ensure that every project has a future. “What if your final-year project could become the foundation for your startup?” I often ask students, and their eyes light up at the possibility.
Real Impact, Not Just Buzzwords
Sometimes, I ask, “What’s the difference with FAVORIOT?”
For me, it’s the focus on solving practical problems. It’s not just another IoT platform; it’s a tool designed to empower users.
One educator shared how FAVORIOT transformed their teaching approach. “Before this, our IoT projects were disconnected. We have a complete ecosystem that lets students see the bigger picture,” they told me.
Hearing that kind of feedback reinforces why we do what we do.
Preparing Students for the 4IR
As we move deeper into the Fourth Industrial Revolution (4IR), IoT skills are no longer optional but essential.
FAVORIOT helps students develop these skills in a meaningful way.
They learn not just how to connect devices but also how to create solutions that can scale and adapt.
And because the platform is affordable, it’s accessible to institutions that might otherwise struggle to provide such opportunities.
A Personal Vision
Creating FAVORIOT wasn’t just about building a product and making an impact.
I often reflect on how my technological journey began with curiosity and access to the right tools.
I wanted to give today’s students the same chance to explore, innovate, and excel. FAVORIOT is more than an IoT ecosystem; it bridges education and industry, ideas and implementation.
Wrapping Up
If there’s one thing I’ve learned, technology is only as good as the problems it solves.
FAVORIOT solves real problems in IoT education and development, empowering users to build solutions that matter.
And for me, that’s what makes all the effort worthwhile.
So, the next time you think about IoT, ask yourself: Are you just building devices, or are you building solutions?
Today, we will explore a structured way to implement IoT projects called the 3-Question Approach (W-W-H). This approach revolves around asking three key questions: What? Why? How?
Let’s review each step to understand how this framework ensures clarity and direction for IoT solutions.
The first question is What? which helps us identify the problem we’re trying to solve.
Purpose: To uncover the actual pain points or gaps in current processes.
Steps:
Look for inefficiencies or challenges in operations.
Identify areas where IoT can provide value.
Examples:
Low production rates in a factory.
Increasing operational costs.
Poor quality control leads to defects.
Safety incidents in a workplace.
Intermittent services in logistics or delivery.
Understanding the problem is the foundation of any successful IoT project.
2. Why? (Objective & End Goal)
Next, we ask Why?, which focuses on the objective and the end goal of the IoT implementation.
Purpose: Clearly define what you want to achieve and align everyone toward that goal.
Steps:
Get buy-in from stakeholders by explaining the benefits.
Ensure the outcome can be monitored and measured effectively.
Examples of Objectives:
Improve logistics and delivery efficiency.
Reduce operational costs.
Enhance asset utilisation and reduce errors.
Boost overall safety and performance.
Defining the “why” ensures a clear purpose behind the IoT deployment.
3. How? (Solutions)
The final question is How? which focuses on the solutions to address the problem and achieve the goals.
Steps:
Use the DNA approach:
D — Device: Identify the right sensors to collect the required data.
N — Network: Choose a suitable network for connectivity (e.g., Wi-Fi, LoRa, 5G).
A — Applications: Develop platforms (mobile or web) to process and display the data.
Decide on an implementation strategy:
Build in-house.
Operate internally.
Outsource to a third party.
Collaborate with partners.
Examples of Solutions:
Install sensors to monitor production lines in real time.
Ensure the network has sufficient coverage and can handle the amount of data.
Develop mobile or web applications to provide actionable insights.
The “how” ensures the project is feasible and actionable.
Key Takeaway
The 3-Question Approach provides a clear path for implementing IoT solutions:
What? — Define the problem.
Why? — Establish the objective.
How? — Develop the solution.
This framework ensures every IoT project is focused, aligned, and effective. Think big, but start small.
Let’s discuss: Can you think of an example where this approach could be applied in your industry or daily life? What “What-Why-How” steps would you take? Share your thoughts!
When I look back on how far IoT has come, I can’t help but feel both amazed and excited. In the early days, IoT was just a concept – a dream of connecting things to improve lives.
But here we are, entering the year 2025, and IoT is no longer just an idea; it’s becoming the backbone of how we live, work, and play.
Let me walk you through what IoT will look like in 2025.
These are not just random guesses but predictions rooted in years of working in this space and observing its evolution.
My answer would be: Not yet, but we’re getting there.
By 2025, IoT will become integral to manufacturing, agriculture, healthcare, energy, and even retail industries.
Factories will use IoT sensors to monitor machinery in real-time, predicting maintenance needs before breakdowns occur.
Farmers will optimise irrigation and fertiliser use through IoT-connected systems, maximising yields while conserving resources.
It’s not just about saving money; it’s about making better decisions.
IoT will help businesses operate more efficiently, reduce waste, and, most importantly, stay competitive in an increasingly digital world.
2. AI-Driven IoT Solutions (AIoT)
When discussing IoT, people often ask, “What about artificial intelligence?”
The truth is that IoT and AI are like two sides of the same coin.
By 2025, the fusion of these technologies – what we call AIoT – will redefine what’s possible.
Imagine traffic lights that adapt to real-time traffic conditions or healthcare devices that predict potential health risks based on continuous monitoring.
This integration will make systems smarter and more autonomous.
Instead of just collecting data, IoT devices will analyse and act on it. It’s not just IoT anymore; it’s intelligent IoT.
3. Sustainability Through IoT
Sustainability is no longer a buzzword – it’s a necessity.
Companies and governments increasingly turn to IoT to tackle environmental challenges.
In 2025, I expect IoT to play a central role in achieving sustainability goals.
For example, IoT-enabled smart grids will help us manage energy consumption more efficiently.
Sensors will monitor air and water quality in real time, allowing us to respond to environmental issues faster.
The idea of a “smart city” is not just about convenience; it’s about creating sustainable and liveable cities. IoT will help us achieve that vision.
4. Proliferation of Edge Computing
Edge computing is something I often talk about when discussing the future of IoT.
It’s a game-changer. Instead of sending all the data to the cloud for processing, edge computing allows devices to process data locally.
This reduces latency and ensures faster responses.
In 2025, edge computing will become indispensable, especially for applications like autonomous vehicles and industrial automation.
Imagine a self-driving car needing to make a split-second decision – there’s no time to send data to a cloud server and wait for a response.
That’s where edge computing comes in.
5. IoT in Healthcare
The healthcare sector is where I see IoT making the most profound impact.
By 2025, wearable devices will go beyond tracking steps or heart rates. They’ll become essential tools for remote patient monitoring.
I envision a world where doctors can receive real-time data about their patients, enabling early intervention and better outcomes.
This is personal because I’ve always believed technology should serve humanity.
IoT in healthcare isn’t just about gadgets; it’s about saving lives and improving the quality of care.
6. Smart Cities Moving Beyond Pilots
If you’ve followed my work, you know I’m passionate about smart cities.
But here’s the thing – many smart city projects are still stuck in the pilot phase.
By 2025, that will change. We’ll see full-scale implementation of IoT solutions for traffic management, utilities, waste management, and public safety.
I often tell people that a smart city isn’t about fancy gadgets; it’s about using technology to make cities more efficient and liveable. IoT will be at the heart of this transformation.
7. IoT Security as a Priority
Let me share a concern that keeps me up at night: IoT security.
As IoT devices become more widespread, they become more vulnerable to cyberattacks.
In 2025, IoT security will take centre stage.
Companies will invest heavily in secure-by-design devices, and blockchain technology may play a role in enhancing protection.
We can’t afford to ignore this. If we want IoT to succeed, security must be a priority.
8. Democratisation of IoT
Here’s an exciting trend: IoT is becoming more accessible.
Low-code and no-code platforms make it easier for small businesses and startups to develop IoT solutions without extensive technical expertise. B
y 2025, I see this trend accelerating, democratising IoT and enabling innovation from unexpected places.
9. IoT for Disaster Management
Climate change is making natural disasters more frequent and severe.
IoT can be a powerful tool for disaster management.
Imagine early warning systems that use IoT sensors to monitor weather conditions in real-time.
In 2025, IoT will play a critical role in disaster preparedness and response especially in cases of flood.
10. Growth of IoT Ecosystems in Emerging Markets
One of the things I’m most excited about is the growth of IoT in emerging markets like Southeast Asia.
By 2025, countries like Malaysia will see a surge in IoT adoption driven by government support and affordable devices.
This will create opportunities for innovation and economic growth.
11. Advanced IoT Analytics
IoT isn’t just about collecting data; it’s about making sense of it.
By 2025, advanced analytics will become a standard part of IoT solutions.
Businesses will use descriptive, diagnostic, predictive, and prescriptive analytics to extract actionable insights, improving decision-making and operational efficiency.
12. National IoT Technology Roadmaps
In Malaysia, we’ve already launched several technology roadmaps focusing on IoT, AI, and blockchain.
By 2025, these roadmaps will guide the development of IoT ecosystems, creating opportunities for local talent and businesses.
13. IoT in Energy and Utilities
Energy efficiency will be a significant focus in 2025.
IoT-enabled smart meters and predictive maintenance systems will help optimise energy usage and reduce waste.
This is not just good for the environment but also for businesses and consumers.
14. Personalised Consumer Experiences
IoT is also transforming retail and marketing.
By 2025, IoT will enable hyper-personalised consumer experiences, using real-time data to predict and meet individual needs.
15. IoT in Education
Lastly, I see IoT transforming education.
Smart classrooms equipped with IoT devices will provide real-time feedback on student engagement and learning outcomes.
This will help educators tailor their approaches to meet the needs of individual students.
Conclusion
These are my predictions for IoT in 2025.
Some may seem ambitious, but I firmly believe we’re heading in this direction.
IoT has the potential to transform industries, improve lives, and create a more sustainable world.
The question is: Are we ready to embrace it?
As someone deeply passionate about IoT, I’m committed to helping make this vision a reality.
The Right Time for Favoriot to Go Global with Its Global Partner Program
Since its inception in 2017, Favoriot has tried empowering IoT developers with a seamless and user-friendly platform.
The Favoriot platform, offered as a B2C solution, has steadily gained traction among developers worldwide, enabling individuals from around the globe to subscribe easily.
By the end of December 2024, the platform had reached an impressive milestone — 111 countries and over 9,200 developers actively leveraging its capabilities.
However, as the IoT ecosystem grew and diversified, it became evident that this was only scratching the surface of Favoriot’s potential.
The question was no longer about whether Favoriot could expand globally but how to scale effectively and make a more significant impact.
While the numbers reflect an inspiring reach, the challenge lies in converting these individual users into broader enterprise implementations. This realisation set the stage for a transformative strategy to take Favoriot’s vision to the next level.
Understanding the Challenges of Going Global
Reaching users overseas is no simple task.
It’s not just about having a great product; it’s about ensuring that the product resonates with the specific needs, regulations, and challenges of different markets.
While the Favoriot platform has always been accessible worldwide, making a lasting impact in foreign markets requires a consistent and relentless marketing effort.
Each country has its complexities, ranging from language barriers to cultural differences and even unique technological and regulatory requirements.
For instance, many countries prioritise data sovereignty, insisting that sensitive data remain within their borders to comply with local policies.
This was a significant hurdle for Favoriot’s initial B2C model, which was designed to operate primarily on a global cloud infrastructure.
The Birth of the Favoriot Enterprise Platform
Recognising these challenges, the team began rethinking its approach.
The solution wasn’t just about increasing subscriptions — it was about localising the platform to better cater to the needs of enterprise clients and government institutions.
This was where the Favoriot Enterprise Platform was born.
Introduced in 2024, the Enterprise Platform was a game-changer for Favoriot. Unlike the traditional model, the Enterprise version was designed to support localised implementations, allowing the platform to be hosted within a country’s borders.
This directly addressed concerns about data sovereignty and compliance with customer policies, making it a more attractive option for large-scale deployments in industries like healthcare, transportation, agriculture, and smart cities.
The platform offers unlimited APIs, with no restrictions on the number of devices connected or APIs utilised, bundled with a perpetual license.
This flexibility and scalability made it a compelling choice for enterprises looking to invest in IoT solutions without worrying about a subscription-based model’s hidden costs or constraints.
The Strategic Role of Global Partners
Launching the Favoriot Enterprise Platform opened up new opportunities and brought a new challenge — how to market and deploy this enterprise-grade solution globally.
The solution is forming partnerships with system integrators and distributors in different countries.
In 2024, Favoriot introduced the Favoriot Global Partner Program, which intends to build a network of trusted partners who could act as system integrators and distributors.
These partners would bring invaluable local expertise, enabling the platform to be tailored to the specific needs of their markets.
The idea was simple but powerful: work with partners who share the same IoT vision and empower them to take Favoriot to new heights in their respective regions.
By becoming the face of Favoriot in their countries, these partners could engage directly with customers, implement the platform, and provide ongoing support.
The partnership model is not just about distribution — it’s about collaboration. Partners can leverage each other’s strengths, engage in cross-selling and cross-marketing activities, and grow their businesses alongside Favoriot.
This creates a win-win situation, fostering mutual growth and ensuring the platform’s success in diverse markets.
Setting Ambitious Goals for 2025
The Favoriot Global Partner Program is not just a short-term strategy; it’s a long-term vision.
For 2025, Favoriot has set an ambitious but achievable goal: to establish partnerships in 25 countries. This means onboarding 25 partners to champion the platform, drive its adoption, and integrate it into their local ecosystems.
Why 25 countries?
This number reflects a strategic focus on markets with high growth potential for IoT.
The program can maximise its impact by carefully selecting partners aligned with Favoriot’s vision and with strong local networks and market knowledge.
Through these partnerships, Favoriot can overcome the barriers of entering foreign markets, such as regulatory hurdles and cultural nuances, while expanding its reach and influence.
The program also enables partners to innovate by combining their local expertise with the technical capabilities of the Favoriot platform.
A Win-Win Strategy for a Global IoT Ecosystem
The Global Partner Program is built on the principle of shared success. For partners, it provides an opportunity to offer a proven IoT platform to their clients, backed by Favoriot’s support and expertise.
For Favoriot, it allows the company to scale its operations without being bogged down by the intricacies of directly managing local markets.
By working with partners, Favoriot can focus on its core mission — empowering IoT developers and enterprises to build smarter, more connected solutions — while its partners drive localisation and implementation.
This synergy is key to the program’s success.
Why Now Is the Right Time
Timing is everything in business, and the decision to go global with the Favoriot Global Partner Program in 2024 couldn’t have been more opportune.
The platform’s footprint in 111 countries and over 9,200 developers demonstrates its global appeal.
However, this traction needs to be converted into tangible enterprise adoption, which the Enterprise Platform and the Global Partner Program are uniquely positioned to achieve.
Furthermore, as IoT continues to gain momentum globally, the demand for localised, scalable, and flexible solutions is growing.
Enterprises are looking for partners who can provide technology and the expertise to implement it effectively.
Favoriot, with its platform and partner-centric strategy, is perfectly poised to meet this demand.
The journey ahead is challenging, but Favoriot is ready to make its mark on the global IoT landscape with the right partners and a clear vision.
The time to go global is now, and Favoriot is stepping forward with confidence, determination, and a strategy that promises growth for everyone involved.
When I first started writing on Medium, I never imagined that it would remind me of the journey I embarked on when I co-founded FAVORIOT.
At first glance, writing and building a startup seem worlds apart.
One is solitary, often involving long hours in front of a screen, while the other demands collaboration, strategic planning, and execution. Y
et, the more I immersed myself in both, the more I realised how strikingly similar the two are.
Allow me to take you through this journey, using my personal experience as both a writer and an entrepreneur.
The Beginning: An Empty Page and a Blank Canvas
Starting a Medium blog is like looking at a blank page.
It’s intimidating.
You have no audience, no reputation, and no guarantee that your words will resonate with anyone. Similarly, building a startup begins with a blank canvas.
You have an idea – a vision – but no customers, no revenue, and no market presence.
I remember the early days of FAVORIOT.
We had a big dream: to help businesses and cities integrate IoT into their operations.
But dreams are just dreams without action.
Writing my first article on Medium felt the same.
I had thoughts swirling in my mind, but translating them into coherent words that others would find valuable was daunting.
Defining Your “Why”
One of the first lessons I learned was the importance of having a clear purpose.
Why was I building FAVORIOT? Why was I writing on Medium?
For FAVORIOT, the purpose was clear: to simplify IoT adoption and empower organisations with data-driven insights.
For Medium, my goal was to share knowledge, inspire others, and document my journey in IoT and entrepreneurship.
Both endeavours required me to articulate my “why” because this became the guiding light when things got tough.
And believe me, things did get tough.
The MVP (Minimum Viable Product)
Every startup begins with an MVP. It’s not perfect – it’s far from it – but it’s functional enough to solve a specific problem for early adopters.
My early articles on Medium were my MVPs.
They weren’t polished masterpieces.
Some were just 500 words, hastily written but filled with genuine insights.
I wrote about IoT trends, startup life, and even personal reflections.
Just as FAVORIOT’s first IoT platform had limited features but solved a critical problem for a niche audience, my initial articles aimed to deliver value to a small group of readers.
The goal wasn’t perfection but progression.
Building an Audience is Like Acquiring Customers
In the startup world, your product is nothing without customers.
Similarly, in writing, your articles mean little without an audience.
Both require a strategy to attract, engage, and retain people.
At FAVORIOT, we identified our target customers – companies and cities that needed IoT solutions – and worked relentlessly to reach them.
On Medium, I did the same. I identified my niche – IoT, smart cities, and entrepreneurship – and wrote consistently within those themes.
But the journey didn’t stop there. Just as a startup founder needs to pitch, network, and build relationships, I had to engage with my readers.
Responding to comments, sharing articles on social media, and participating in discussions were all crucial in growing my Medium audience.
The Grind: Consistency Over Time
Building a startup and writing regularly both demand one thing above all: consistency.
There were days when it felt like no one cared about what I was building at FAVORIOT.
Months would go by with no significant sales or partnerships.
Similarly, there were weeks when my articles on Medium received little to no views.
It’s disheartening.
But success doesn’t happen overnight. I learned to embrace the grind.
At FAVORIOT, we kept refining our platform, reaching out to potential clients, and showcasing our value proposition.
On Medium, I kept writing, experimenting with different formats and topics, and learning what resonated with my readers.
Consistency builds momentum. And momentum is what drives growth.
Feedback is Gold
In both ventures, feedback is invaluable.
For FAVORIOT, customer feedback shaped our product development.
It told us what features to add, what to fix, and what to prioritise.
For my Medium writing, reader feedback was equally crucial.
When readers left comments or shared my articles, it gave me insights into what worked and what didn’t.
Some feedback was critical, but I welcomed it. Just as a startup must listen to its customers, a writer must listen to their audience.
Scaling Up
Once you’ve found your footing, the next challenge is scaling.
For FAVORIOT, scaling meant expanding our platform’s capabilities, entering new markets, and forming global partnerships.
For my Medium writing, scaling meant increasing my output, diversifying my topics, and reaching a broader audience.
But scaling comes with its own challenges.
In a startup, you risk losing focus as you try to do too much too quickly. The same is true for writing.
At one point, I tried writing about topics outside my expertise, thinking it would attract more readers. It backfired.
I learned that scaling isn’t just about doing more; it’s about doing more of what you do best.
The Role of Passion
Both writing and building a startup require passion.
Without it, you’ll struggle to persevere through the inevitable challenges.
I’m deeply passionate about IoT and its potential to transform industries and improve lives.
This passion drives my work at FAVORIOT. It’s the same passion that fuels my writing on Medium.
When you’re passionate, it shows. Customers sense it. Readers sense it.
Passion isn’t something you can fake – it’s either there, or it isn’t.
The Payoff
After years of hard work, FAVORIOT is now recognised globally, with partners in multiple countries.
Similarly, my writing on Medium has garnered a loyal following, with some articles reaching thousands of readers.
The payoff isn’t just financial or numerical.
It’s the satisfaction of knowing you’ve built something meaningful.
For FAVORIOT, it’s the impact we’ve had on businesses and cities.
For my writing, it’s the messages I receive from readers who say my articles inspired them.
Final Thoughts
Writing on Medium and building a startup are both about creating value.
They require courage, resilience, and a willingness to learn.
If you’re considering starting a blog or launching a business, remember this: start small, be consistent, and never lose sight of your purpose.
The journey may be challenging, but the rewards are worth it.
Looking back, I’m grateful for both experiences.
They’ve taught me invaluable lessons, shaped my perspective, and allowed me to connect with amazing people.
And who knows?
Maybe your journey as a writer or entrepreneur will inspire others, just as mine has inspired me.
Artificial Intelligence (AI) and Big Data Analytics have become the talk of the town.
Everywhere I go, someone discusses how these technologies are transforming industries and reshaping how organisations work.
But let me tell you, all of this innovation boils down to one thing: data. AI can’t learn without data, and analytics can’t deliver insights.
This realisation has enormous implications for how universities prepare students and educators for the future.
Over the years, many universities have focused on teaching students to build their Internet of Things (IoT) hardware.
Don’t get me wrong, it’s a great way to learn the technical basics, but I’ve always felt it’s not the best use of resources or time.
The truth is that the hardware is just a means to an end.
The real value is in the data these devices collect and what you do with that data. That’s where I think universities should shift their focus: data analytics and AI.
Why Data is the Real Hero in AI and Big Data Analytics
Here’s the thing about AI: it’s only as good as the data you feed.
Whether you’re predicting customer behaviour, analysing health trends, or optimising supply chains, the first step is always about collecting, cleaning, and understanding data.
And guess what generates a lot of that data? IoT devices.
From smart sensors to wearables, these devices are constantly collecting information streams. But the value isn’t in the device; it’s in the insights you can extract from the data.
Take smart cities, for example. IoT sensors might monitor traffic flow, air quality, or energy usage.
That’s impressive, but more amazing is how AI models and analytics make sense of all that data to improve city living.
Building the hardware for these sensors is straightforward; developing the AI and analytics platforms behind them is the real challenge.
Why Universities Need to Prioritise Data Analytics
1. Meeting Industry Needs
Let me be honest — the industry doesn’t need more people building IoT hardware.
They’re hungry for data analysts, AI developers, and data scientists. Companies are about insights that drive decisions, not the physical gadgets that generate the data.
Shifting the focus to data analytics would better prepare students for what’s waiting for them in the real world.
2. Endless Applications
Consider this: data analytics and AI can be applied across many industries. Whether it’s healthcare, agriculture, manufacturing, or retail, the possibilities are endless.
With skills in data analytics, students can work on anything from predicting machinery maintenance to forecasting disease outbreaks or personalising customer experiences.
Meanwhile, hardware skills are mostly limited to niche engineering roles.
3. Lowering Barriers to Entry
Let’s face it: building IoT hardware isn’t cheap. You need tools, components, and a workshop.
That’s a big ask, especially for students or universities with limited budgets.
In contrast, data analytics only requires access to software tools, cloud platforms, and datasets, which are much more accessible.
4. Using What’s Already Available
These days, you don’t even have to build IoT devices from scratch.
There are ready-made solutions, like FAVORIOT, AWS IoT, and Azure IoT.
These platforms make collecting, storing, and managing IoT data easy. So why reinvent the wheel? Use these tools and focus on creating value through analytics and application development.
How Universities Can Make the Shift
1. Rethink the Curriculum
If I were designing a university course, I’d ensure it included data analytics, AI, and IoT platforms. Students should learn how to:
Collect and preprocess IoT data.
Use tools like Python or MATLAB to analyse data.
Build machine learning models and deploy them in real-world scenarios.
Understand cloud computing and work with IoT platforms to manage data.
2. Partner with Industry
One of the smartest moves universities can make is partnering with companies. Industry collaboration gives access to real-world datasets, tools, and expertise.
Plus, internships and collaborative projects can give students the hands-on experience they need to hit the ground running.
3. Focus on Real-World Problems
When I was a student, I always enjoyed projects that felt meaningful.
Educators should design projects that challenge students to solve actual problems.
For example, they could predict energy usage patterns on campus or analyse traffic data to improve transportation systems.
4. Train the Trainers
Let’s not forget the educators.
They need to stay ahead of the curve, too.
Universities should invest in training programmes for lecturers, helping them stay updated on the latest AI and data analytics trends.
5. Provide the Right Tools
Students can’t learn data analytics without the right tools.
Universities should give them access to software, cloud-based platforms, and open-source datasets. This doesn’t have to break the bank — many affordable or even free options exist.
Imagine the Applications Students Can Build
By focusing on data analytics, students can work on exciting applications like:
Smart Agriculture: Analysing soil and weather data to optimise irrigation and fertilisation.
Healthcare: Using wearable data to predict health trends.
Retail: Analysing customer behaviour to personalise shopping experiences.
Manufacturing: Implementing predictive maintenance to cut costs and downtime.
These examples show how data analytics can drive innovation across industries.
Isn’t that more impactful than soldering circuit boards?
My Advice to Universities
The world is changing fast, and universities need to keep up.
It’s time to move away from DIY IoT hardware and focus on the bigger picture: data analytics.
By doing this, universities can prepare their students for a future where data is king.
As educators, it’s our job to help students see the actual value of IoT — not the gadgets but the insights they enable.
And for students, my advice is simple: dive into data analytics and AI. These skills will open doors and help you make a real difference.
The future is all about harnessing the power of data.
Let’s make sure our universities are ready to lead the way.
Today, we will explore a simple and practical framework for implementing IoT projects: the 3-Step Approach.
This method ensures a smooth and effective rollout by focusing on small steps, integration, and innovation. Let’s break it down step by step.
Step 1: Think Big, Start Small
The first step is to start with a clear vision (think big) but begin with a small, focused project to gain momentum.
Develop a Small Application: Identify one specific problem and build a targeted solution.
Example: A smart thermostat to monitor energy usage in one building rather than an entire campus.
Deliver Immediate Impact: The solution should show quick results to build confidence in IoT’s value.
Mindset Transformation: This small success shifts how people perceive IoT and its potential.
Get Buy-In from Leadership: Demonstrating early results helps secure support from decision-makers like the C-suite executives for future projects.
Step 2: Integrate
Once the initial IoT solution proves its value, it is integrated into the broader system.
Connect to Legacy Systems: Ensure the new IoT solution works seamlessly with existing infrastructure, such as ERP systems or older databases.
Example: Integrating smart sensors into a factory’s traditional production line.
Seamless Workflow: Avoid disrupting operations by designing smooth processes between old and new systems.
Break Silos: Encourage collaboration between departments to maximise the benefits of IoT across the organisation.
This step ensures that IoT doesn’t operate in isolation but becomes a part of the larger ecosystem.
Step 3: Innovate
The final step is to use IoT to drive innovation and create new opportunities.
Create New Workflows: Leverage IoT to optimise or redesign how work is done.
Example: Using real-time data from IoT sensors to automate maintenance schedules.
Test New Business Models: Experiment with different ways to generate revenue using IoT solutions.
Example: Offering predictive maintenance as a subscription service for customers.
Better Analytics and AI: Use advanced analytics and AI to unlock deeper insights from IoT data and automate decision-making.
This stage transforms IoT from a problem-solving tool into a driver for long-term growth and innovation.
Key Takeaway: Think Big, Start Small
The overall lesson is simple:
Start with a big vision, but focus on small, impactful projects to get started.
Build on early successes by integrating solutions into larger systems.
Use IoT to innovate and create new opportunities.
This approach minimises risk, builds momentum, and ensures sustainable growth.
Let’s discuss: What small IoT applications can you think of to start with? How would you scale and integrate them into a more extensive system? Let’s brainstorm together!
Dr. Mazlan Abbas 