Tag: IoT

From Teaching IoT to Solving Real Problems: Lessons I Learned the Hard Way

Looking back at my years of building IoT solutions, I can see how much the conversation around IoT has changed. In the beginning, our challenge was convincing people that IoT mattered. Later, people wanted to learn how to build it themselves. Today, building an IoT prototype has become much easier, especially with generative AI helping people write code and solve technical problems. Yet one uncomfortable reality remains: the IoT market has not grown as quickly as many of us expected.

That experience has forced me to rethink what customers actually need from IoT. After years of developing FAVORIOT, conducting training, working on projects and watching pilots succeed technically but struggle commercially, I have learned that the biggest challenge is rarely the technology itself. The harder question is whether we are solving an operational problem that matters enough for someone to take ownership, allocate a budget and keep the solution running.

The Early Days Were About Explaining IoT

In the early days, many of our conversations started with a basic question: “What is IoT?” People had heard the term, but few understood how sensors, connectivity, cloud platforms and applications could work together. We spent considerable time educating customers, students and organisations about what IoT could do and why connecting physical assets could change the way operations were monitored.

At that time, simply demonstrating the technology could create excitement. When someone saw a sensor transmitting data to a cloud platform and displaying the information on a dashboard, it felt like something new. We could demonstrate remote monitoring, automatic alerts and real-time data collection, and people immediately became curious about the possibilities. We believed that once awareness increased, adoption would naturally follow.

Then People Wanted to Build IoT Themselves

As awareness grew, the questions changed from “What is IoT?” to “How can I build an IoT solution?” This created another chapter for FAVORIOT, where training became an important part of what we did. We conducted many IoT programmes involving sensors, Arduino, ESP32, Raspberry Pi, MQTT, cloud platforms, dashboards and application development.

The appetite for learning was strong because people wanted practical experience. Students wanted to build projects, lecturers wanted to introduce IoT into teaching and research, while engineers and professionals wanted to understand how connected systems could be applied in their organisations. IoT was gradually moving from something people heard about at conferences into something they could actually build with their own hands.

Then generative AI arrived, and we noticed another shift. Demand for traditional IoT training appeared to decline. One possible reason is that people can now ask an AI assistant how to connect an ESP32, generate MQTT code, troubleshoot an error or explain how a sensor works. Knowledge that once required attending a two-day workshop can now be accessed within minutes.

If IoT Is Easier to Build, Why Is the Market Still Slow?

This became an uncomfortable question for many IoT solution providers, including us. Sensors became cheaper, connectivity improved, platforms matured and technical knowledge became easier to obtain. Generative AI lowered the technical barrier even further, yet the commercial market for IoT still seemed to move much more slowly than the technology.

For a long time, we believed demonstrating stronger technology would help overcome this problem. We showed customers devices, dashboards, alerts, analytics and different ways of connecting physical assets. A good demonstration could attract attention, lead to discussions and sometimes result in a pilot project. Technically, many of these pilots worked exactly as expected.

The problem came afterward. Some pilots simply stopped. The sensors were working, data was flowing and dashboards were displaying information, yet the project never expanded. We slowly realised that proving technology could work was very different from proving that an organisation needed it badly enough to continue investing in it.

A Successful Pilot Can Still Become a Failed Project

That experience taught us to ask a different question: who owns the project after the pilot? Someone might approve an experiment, another department might provide the equipment and an IT team might help with connectivity, but nobody may actually be responsible for turning the pilot into part of daily operations.

Without operational ownership, a pilot can easily become a technology showcase rather than a working system. If nobody is accountable for the problem being addressed, nobody feels enough urgency to expand the solution. There may also be no operational budget, measurable outcome or internal champion willing to push the project beyond its experimental stage.

This changed the questions I now believe we should ask at the beginning of an IoT project. What operational problem is the customer experiencing? Who suffers when that problem occurs? What does the organisation lose when the problem remains invisible? Who receives the information generated by the system, and what action will that person take? Most importantly, who owns the outcome after the pilot finishes?

Customers Rarely Wake Up Wanting IoT

A maintenance manager probably does not arrive at work thinking about buying an IoT platform. He may simply want to know whether a remote pump has stopped running before someone complains. A facilities manager may want to understand why electricity consumption suddenly increased, while an environmental officer may need an early warning when water quality begins moving outside acceptable limits.

The same applies to energy systems, buildings, factories and remote assets. Customers are usually concerned about downtime, wasted energy, unnecessary site visits, equipment failures, delayed responses and things happening in their operations that they cannot see quickly enough. IoT becomes valuable when it helps expose those problems early enough for someone to act.

This has changed the way I think about FAVORIOT as well. Connecting devices remains necessary, but connection alone is not the outcome. Data must help someone see something they could not previously see, understand what is happening and decide what to do next. That is why Connect → See → Act represents something much deeper to me today than simply describing how an IoT platform works.

Lessons I Learned the Hard Way

After years of explaining IoT, teaching people how to build it, developing our own platform and watching projects move through different stages, several lessons have become difficult to ignore.

  1. Awareness does not automatically create demand. Someone can understand IoT very well without having a strong enough operational reason to buy a solution.
  2. Technical success is different from commercial success. Getting a sensor to transmit data and displaying it beautifully proves that the technology works. It does not prove that the organisation will continue paying for it.
  3. Every pilot needs an operational owner. Someone inside the customer’s organisation must care about the outcome, be responsible for the problem and have enough influence to move the project forward.
  4. Start with the pain, not the platform. Conversations about downtime, energy losses, unnecessary site visits, equipment failures and delayed responses are usually more meaningful than conversations about protocols, dashboards and technical specifications.
  5. IoT creates value when visibility leads to action. Collecting more data is not enough. The real value comes when information helps someone recognise a problem earlier and respond before the consequences become more expensive.

Perhaps this has been one of the hardest lessons from building IoT solutions over the years. We spent the early years proving that IoT technology worked. We then spent years teaching people how to build it. Today, I believe the conversation has to move beyond both.

The future of IoT will not be decided by how many sensors we can connect or how impressive our dashboards look. It will be decided by whether we can help organisations see operational problems they could not see before and give the right people enough information to act.

That lesson took years of projects, pilots, training programmes, successes and disappointments for me to fully appreciate. Stop trying to sell customers IoT. Find the operational problem they desperately need to see, and make that problem visible.

Favoriot Sembang Santai (Episodes 1 – 58) Hosted by Mazlan Abbas and Zura Huzali

This is the part of the list compilation of Favoriot Sembang Santai Podcasts. They are available in YouTube, Spotify and Amazon.

Favoriot Sembang Santai — Mazlan Abbas & Zura Huzali
FAVORIOT PODCAST DIRECTORY

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Sembang Santai

Episodes featuring Zura Huzali with Dr. Mazlan Abbas. Browse the series in episode sequence and jump to YouTube.

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IoT Platforms: The Heart of Every Smart Solution

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Favoriot Sembang Santai • Hosted by Zura Huzali with Dr. Mazlan Abbas • Directory prepared 17 September 2026

Are Your Potential Customers Ghosting You? 8 Warning Signs Every Business Owner Should Know

It usually begins with excitement.

The first meeting goes extremely well. Everyone has ideas. The customer talks about a pilot project, future deployment, possible collaboration and even a long-term partnership. People use words such as “promising,” “interesting,” and “we should definitely explore this further.”

You leave the meeting thinking, “This one looks serious.”

Then you send the proposal.

Silence.

You follow up a week later.

Still silence.

At some point, even the crickets give up.

Welcome to one of the most frustrating experiences in business: being ghosted by a potential customer or partner.

8 Signs Your Business Opportunity May Be Fading Away

1. Their Replies Become Shorter and Slower

At the beginning, their messages were detailed and enthusiastic. They asked questions, suggested ideas and wanted more information. Replies arrived quickly because there was genuine momentum.

Then something changes.

Long messages become “Noted,” “Will check,” “Let me discuss internally,” or the legendary phrase:

“We will get back to you.”

The problem is not the phrase itself. The problem begins when nobody knows when “get back to you” is supposed to happen.

2. “Next Week” Never Arrives

“We should be able to confirm next week.”

You wait.

One week becomes two. Two weeks become a month. Three months later, you begin wondering whether their calendar operates in a different time zone from the rest of humanity.

In business, dates matter because dates indicate commitment. If every next step has no specific date attached to it, the opportunity may already be sliding down their priority list.

3. You Are the Only Person Following Up

There is a simple way to test the health of an opportunity.

Stop messaging for a while.

If the entire conversation immediately goes into hibernation, you may already have your answer.

A genuine business opportunity normally has movement from both sides. You provide information, they respond. They ask questions, you answer. You submit something, they review it. Someone proposes the next meeting.

If you are constantly the person restarting the conversation, you may not be managing an opportunity anymore. You may be performing CPR on one.

4. Meetings Keep Getting Postponed

One postponement is normal. People are busy and unexpected things happen.

The warning sign appears when meetings are repeatedly postponed without a replacement date.

Then comes another famous phrase:

“Let’s reschedule soon.”

Of course.

“Soon” must be one of the most popular dates in business. It sounds positive while committing to absolutely nothing.

5. They Love the Idea Until the Quotation Arrives

This is where excitement meets reality.

During the presentation, everyone loves the technology. During the demonstration, people are impressed. When discussing possibilities, the future sounds wonderful.

Then you send the quotation.

Suddenly, their Wi-Fi appears to stop working.

This is when we learn an important distinction: interest is not buying intent.

Someone can genuinely like your idea without having the budget, authority, urgency or internal support required to purchase it.

6. They Keep Asking for Documents, but Never Make a Decision

Proposal? Sent.

Quotation? Sent.

Presentation? Sent.

Technical architecture? Sent.

Company profile? Sent.

Revised quotation version two, three and four? Also sent.

The decision?

Apparently still travelling somewhere between departments.

One lesson I have learned is that more document requests do not necessarily mean you are getting closer to winning the project. Sometimes they simply mean you are doing more unpaid work.

7. Nobody Else Joins the Conversation

This is one signal I pay much more attention to today.

When an opportunity becomes serious, the circle usually expands. The technical team wants to understand the solution. Management starts asking business questions. Procurement appears. Finance discusses budget. Legal may eventually review the agreement.

These are signs that the opportunity is moving through the organisation.

But if months have passed and you are still speaking to one very friendly contact who keeps discussing how wonderful the partnership could become, be careful.

You may not have a business opportunity yet.

You may simply have a very friendly person who likes your idea.

8. They Are Active Everywhere Except in Your Inbox

This one can be both funny and painful.

They have time to post on LinkedIn.

They upload photos from events.

They congratulate someone on a promotion. They comment on AI. They like conference announcements.

Meanwhile, your message remains peacefully unread or unanswered, apparently enjoying a long meditation retreat.

At some point, the message itself becomes the message.

Silence Does Not Always Mean Rejection

We should not assume too quickly that someone is deliberately ignoring us. Business situations can change unexpectedly.

Budgets get frozen. Management changes. A project loses its internal sponsor. Procurement gets delayed. Another project becomes more urgent. Sometimes the person we are dealing with genuinely does not have an answer yet.

That is why I do not believe in immediately becoming angry or burning the relationship.

At the same time, we must respect our own time and resources.

If an opportunity has no next step, no date, no owner and no action, we need to consider the possibility that it is simply no longer a priority.

Give Them One Final Opportunity to Be Clear

Instead of sending endless messages asking, “Any update?”, I prefer a final message that makes the choices clear:

“We had a good discussion about this opportunity, but I understand that priorities may have changed. Would you prefer to proceed, pause the discussion until a specific date, or close it for now? A direct answer is perfectly fine as it helps us plan our resources.”

This gives the other party three simple choices:

  1. Proceed because there is still genuine interest.
  2. Pause until a specific and realistic date.
  3. Close the opportunity and revisit it someday if circumstances change.

A “no” may hurt for a few minutes. Months of uncertainty can waste far more time.

If They Still Do Not Reply, Move On

There comes a point when another follow-up will not change anything.

Move the opportunity out of your active pipeline. Stop spending emotional energy on it. Keep the relationship professional and leave the door open, but focus your attention on customers and partners who are willing to move.

Do not keep watering a plastic plant.

One of the harder lessons in business is learning that enthusiasm during a meeting is not the same as commitment after the meeting.

People can smile, praise your presentation, talk about huge possibilities and sound genuinely excited. None of those things require much commitment.

What happens after the meeting tells you far more.

Do they introduce you to the decision-maker? Do they arrange the next meeting? Do they discuss the budget? Do they involve procurement? Do they agree on a pilot date? Do they actually do what they said they would do?

That is where genuine interest becomes visible.

People can be incredibly excited during a meeting. Real interest shows after the meeting, when they are willing to take the next step.

In business, learn to appreciate enthusiasm.

But learn to recognise commitment.

I Pitched My Elderly Monitoring Startup to Nearly 100 Investors. Here’s Why They All Said No

Before FAVORIOT became known for its IoT platform and Operational Visibility Platform, our first product was something very different. It was called Favorwatch, an elderly-monitoring solution that we began developing in 2017.

Favorwatch used a smartwatch to monitor the health, safety and location of elderly people living independently. Its geofencing feature could alert family members or caregivers when the wearer moved beyond a designated area. We summarised its purpose with a simple promise: “Live alone, but never be left alone.”

The product addressed a genuine social concern. Families were becoming more geographically dispersed, ageing populations were growing and wearable technologies were becoming more capable. We believed Favorwatch could help elderly people preserve their independence while giving their families greater peace of mind.

It was a meaningful idea. But a meaningful idea does not automatically become a sustainable business.

I Was Pitching the Future, Not the Evidence

During the early stages, I presented Favorwatch at accelerator demo days and pitched it directly to investors whenever opportunities appeared. I spoke about ageing populations, remote healthcare, wearable devices and the need to protect elderly people living alone.

The story was convincing, but the business was still immature. Our presentation described what Favorwatch could become, while investors wanted evidence of what it had already achieved.

I sent the pitch deck to nearly 100 venture capital firms, investors and related companies. Most never responded. A small number replied, but every response ended in rejection.

At first, I wondered whether investors simply did not understand the opportunity. We were early, the concept was uncommon and the market appeared likely to grow. With time, I realised that the problem was not necessarily their understanding of the idea.

They could see the potential. They could not see enough proof that customers were willing to pay.

Everyone Liked It Until We Discussed Payment

One of the most confusing experiences for a founder is receiving positive feedback without generating sales. Many people told us that Favorwatch was useful, meaningful and promising. They understood why families would want to protect elderly relatives through wearable monitoring.

The enthusiasm weakened when the conversation moved from appreciation to payment.

That exposed the difference between supporting an idea and buying a product. Families cared about elderly safety, but many were comfortable relying on telephone calls, relatives or existing caregiving arrangements. Healthcare organisations could recognise the value but might not have a budget, procurement route or person responsible for purchasing the solution.

People saying, “This is a good product,” sounded encouraging. It was not the same as saying, “Where do I sign, and how much should I pay?”

The Questions We Had Not Answered

Looking back, our challenge was not caused by a single mistake. Several business questions remained unresolved:

  1. Who was the actual customer? The elderly person used the product, but an adult child might pay for it. A care centre might manage it, while a healthcare provider could benefit from the data.
  2. Was the problem urgent enough? Elderly safety mattered, but concern did not always lead to immediate purchasing decisions.
  3. Was the business model workable? Device costs, connectivity, subscriptions, support and customer service affected both the selling price and profitability.
  4. Was the product ready for continuous use? A successful demonstration did not prove reliability, battery performance, network coverage or user acceptance over many months.
  5. Could we demonstrate repeatable demand? We did not have enough paying customers or dependable sales channels to show that the business could grow.

These gaps made the investment risk too high. Investors were not rejecting the social purpose of Favorwatch. They were rejecting the absence of market traction.

From Favorwatch to Raqib

Favorwatch later evolved into Raqib, a monitoring solution for Hajj and Umrah pilgrims. The target market changed, but the core purpose remained: using wearable technology, location tracking and geofencing to keep people safe and connected.

The pilgrimage market offered a more specific use case. Pilgrims could become separated from their groups, experience health problems or struggle to communicate their location in crowded environments. We tested Raqib locally and with early users, and I personally tested it during Umrah.

The pivot gave us greater market clarity, but it did not remove every commercial risk. Even a focused product requires committed buyers, suitable pricing, trusted partners and good timing.

What I Would Tell My Earlier Self

If I could advise the founder who sent those 100 pitch decks, I would not tell him to stop. I would tell him to spend more time proving customer demand before seeking investment.

I would ask:

  • Who owns the problem and controls the budget?
  • What happens if the customer takes no action?
  • Will the customer pay for a pilot?
  • Can we measure the financial or operational value?
  • Can we win five similar customers without rebuilding the product?
  • Will the revenue cover delivery, support and future development?

Those investor rejections were painful, but they exposed weaknesses that compliments had concealed. They taught me that praise is not market validation, interest is not traction and a successful pitch is not a substitute for a paying customer.

A founder needs conviction to keep building through uncertainty. Yet conviction must eventually be supported by evidence. The market validates a product when customers commit their money, time and reputation to using it.

That was the lesson Favorwatch gave me long before FAVORIOT became the company it is today.

Why I Started Calling It Operational Blindness

“There has to be a better way to describe what I’ve been seeing.”

For years, that thought kept returning whenever I met customers. It followed me into boardrooms, factories, utility plants, government agencies, and Smart City command centres. Every meeting seemed different on the surface, yet they all ended with a similar feeling that something important was missing.

At first, I believed the problem was technology. I thought organisations simply needed more sensors, better connectivity, or a more capable IoT platform. Later, as artificial intelligence became the latest trend, I wondered if AI would finally solve the problem that had frustrated me for years.

The more I observed, the more I realised I had been asking the wrong question. The problem was never about having more technology. It was about why organisations continued making poor operational decisions despite having so much technology around them.

The Promise That Didn’t Match Reality

When I co founded Favoriot, I genuinely believed that if organisations could connect their devices and continuously collect operational data, better decisions would naturally follow. It sounded logical because connected systems should produce better visibility, and better visibility should improve operations.

That belief shaped much of our early thinking. We focused on connecting sensors, collecting data, building dashboards, and making information available in real time. Technically, everything worked exactly as we intended.

Then I started spending more time with customers.

Everything Looked Digital

I visited factories with sophisticated production monitoring systems. I walked into utility control rooms filled with SCADA screens and large video walls. I met building operators who proudly demonstrated their Building Management Systems, while Smart City command centres showcased dashboards that displayed hundreds of live data feeds.

Everything looked impressive. From the outside, these organisations appeared highly digital, highly connected, and fully in control. If someone judged only by the technology they saw, they would probably conclude that these organisations had already solved their operational challenges.

Yet the conversations told a completely different story.

The Same Answers Everywhere

Whenever I asked simple operational questions, I kept hearing remarkably similar responses.

“We’re still investigating the root cause.”

“Nobody realised the equipment had been deteriorating.”

“The maintenance team wasn’t informed in time.”

“Operations thought Engineering was handling it.”

“We have the data, but we’ll need time to retrieve it.”

These weren’t isolated incidents. They appeared in manufacturing, water utilities, agriculture, energy, healthcare, environmental monitoring, and Smart City projects. Different industries were using different technologies, but they were all struggling with surprisingly similar operational problems.

Technology Wasn’t the Missing Piece

As an engineer, I naturally tried to solve the problem by looking at the technology. Perhaps organisations needed more sensors. Perhaps they needed more dashboards or more sophisticated analytics. When AI became widely available, I even wondered whether intelligent algorithms would finally close the gap.

But the gap remained.

The more technology organisations deployed, the more puzzled I became. Multi million ringgit projects still depended on phone calls to verify incidents. Teams still relied on WhatsApp groups during operational emergencies. Reports still arrived after problems had already caused financial losses, and managers continued making decisions using fragmented information collected from disconnected systems.

The Frustration Started Growing

There were many evenings when I drove home replaying customer conversations in my head. Why does this keep happening? Why are organisations still surprised by problems they should have detected much earlier? Why do sophisticated dashboards still fail to prevent operational failures?

Those questions stayed with me because I couldn’t find a satisfying answer. Every new customer seemed to reinforce the same pattern instead of challenging it. It became increasingly difficult to believe that another dashboard or another AI model would somehow solve the underlying issue.

Slowly, I realised that I wasn’t looking at a technology problem. I was looking at something much deeper.

It Was Never About Data

One of the biggest turning points came when I realised organisations were not suffering because they lacked data. In fact, many had more operational data than they knew how to use. Sensors, PLCs, SCADA systems, ERP platforms, and IoT solutions were already generating enormous amounts of information every second.

The problem was that data does not automatically create understanding. Thousands of sensor readings cannot explain which issue deserves immediate attention. Beautiful dashboards cannot tell people which decision will prevent tomorrow’s failure. Artificial intelligence cannot produce reliable recommendations when operational information is incomplete, delayed, or disconnected from business context.

What organisations lacked was not data.

They lacked operational visibility.

Finding the Right Words

The phrase didn’t appear during a conference or while preparing a presentation. It arrived during one of those quiet moments when years of observations finally began connecting together.

This isn’t a data problem.

This isn’t an IoT problem.

This isn’t even an AI problem.

People are making decisions without seeing the complete operational reality.

Almost immediately another thought came to mind.

They’re operationally blind.

Operational Blindness.

The moment I spoke those words, everything suddenly made sense.

Suddenly the Pattern Was Obvious

Operational Blindness explained why organisations reacted instead of anticipated. It explained why departments worked in isolation despite sharing the same objectives. It explained why dashboards could display everything in green while operational performance quietly deteriorated underneath.

I began seeing Operational Blindness everywhere. A leaking pipeline that remained unnoticed until millions of litres of treated water had been lost. A machine whose vibration gradually increased until production stopped unexpectedly. A hospital where maintenance records were scattered across disconnected systems. A commercial building where energy costs quietly increased month after month because nobody recognised abnormal patterns early enough.

Different industries. Different technologies.

Exactly the same operational condition.

It Changed How I Saw Favoriot

That realisation also changed how I described our own company.

For years, I introduced Favoriot as an IoT platform because that was technically correct. Over time, I realised customers were rarely looking for another platform. They were looking for a way to stop recurring operational surprises, reduce uncertainty, and gain confidence in their daily decisions.

Customers don’t buy dashboards simply because they look attractive. They invest because they want fewer failures, lower operating costs, better compliance, improved reliability, and stronger business outcomes. The platform is only one part of that journey.

A Bigger Mission

Today, I no longer see Favoriot simply as a company that connects devices. I see it as helping organisations reduce Operational Blindness by connecting fragmented operational data, providing meaningful context, supporting faster decisions, and enabling coordinated actions across different teams.

That mission extends beyond IoT. It applies equally to manufacturing, utilities, healthcare, agriculture, logistics, smart buildings, critical infrastructure, ESG reporting, and even cybersecurity. Wherever operational decisions depend on trusted information, Operational Blindness can exist.

As artificial intelligence becomes increasingly capable, this challenge becomes even more significant. AI cannot compensate for missing operational context, disconnected information, or delayed data. Before organisations can become AI driven, they must first become operationally aware.

More Than Just a New Phrase

Looking back, I sometimes smile at how long it took me to recognise what had been sitting in front of me all along. I thought I was building an IoT platform, but what I was really trying to solve was a much larger operational problem that existed across almost every industry.

The phrase Operational Blindness represents years of customer conversations, personal frustrations, lessons learned, and moments of clarity. It gave me a way to describe a problem that many organisations experience every day but struggle to explain.

Perhaps the most meaningful breakthroughs don’t always come from inventing new technologies. Sometimes they come from finding the right words to describe a challenge that everyone has experienced but nobody has been able to name.

Have you ever experienced Operational Blindness in your own organisation? I would love to hear your story because every experience helps us understand this challenge better, and every lesson brings us one step closer to building organisations that can truly connect, see, and act.

Malaysia’s IoT Market Has The Infrastructure. So Why Is Adoption Still Crawling?

Every few months a new market research report lands in my inbox with a headline number for Malaysia’s IoT market. Billions of dollars. Double-digit CAGR. Smart city spend projected to grow at 27% a year through 2034. On paper, we look like a country sprinting toward a connected future.

I have been in this industry long enough, from MIMOS to REDtone IoT to building FAVORIOT from scratch, to know the difference between a market projection and a market. The projection is what analysts model when they extrapolate 5G rollout numbers and government budget announcements. The market is what actually gets deployed, paid for, and kept running past the pilot phase. In Malaysia right now, there is a real gap between the two, and I think it is worth naming exactly where that gap comes from.

The Infrastructure Story Is Genuinely Good

Let’s give credit where it belongs first, because the connectivity layer has moved fast. 4G coverage sits above 96% of populated areas. 5G adoption crossed 52% by the end of 2024, and coverage reached over 82% of populated areas by 2025. Malaysia has more than 7,000 5G sites deployed and pulled in over RM86 billion in data center investment in 2024 alone, making the country Southeast Asia’s leading data center hub.

That is not a small achievement. A country cannot build an IoT economy without pipes to carry the data, and Malaysia’s pipes are, by regional standards, excellent. If you had told me in my MIMOS days that we would have this level of physical infrastructure by 2026, I would have been thrilled.

But infrastructure was never the constraint. Demand was.

The Roadmap We Wrote, And The Reality We Got

Go back to the National IoT Strategic Roadmap, the document MIMOS helped shape more than a decade ago. It forecast IoT applications and services reaching RM34 billion by 2025, up from RM7.5 billion in 2020. Device production was projected to hit RM4.3 billion in the same window.

Nobody in this industry seriously believes we hit those numbers. I do not say that to be cynical about the roadmap. I say it because the gap between what we projected and what materialized is the single most instructive data point in this entire market. It tells us the bottleneck was never technological capability. It was adoption discipline, and adoption discipline is a much harder problem to solve with a budget allocation.

Seven Reasons Growth Keeps Stalling

I want to walk through the actual mechanics of why, because “slow adoption” is too vague to act on. Here is what I see happening on the ground, backed by what the data confirms.

SMEs are still building the foundation IoT depends on. Malaysia’s economy runs on small and medium enterprises, and a recent survey found only about 35% of surveyed SMEs had implemented basic digital systems beyond simple accounting software. You cannot sell predictive maintenance sensors to a factory floor that has not digitized its production logs yet. IoT vendors keep pitching step five to companies that are still working through step one, and the pitch lands as noise rather than opportunity.

The payback math does not match buyer expectations. Deploying an IoT platform requires real upfront investment in hardware, software, and integration with legacy systems, and for SMEs this cost is a genuine barrier to entry even when the long-term ROI is positive. Malaysian buyers, especially in manufacturing and plantation sectors, want a return inside 12 to 18 months. Most honest business cases for connected infrastructure deliver in 24 to 36. That gap kills deals at the finance desk long before the technical evaluation even starts.

We have a talent bottleneck on both sides of the table. Adoption requires skills in IoT, data analytics, cybersecurity, and cloud computing, and Malaysia faces a real shortage of professionals who can manage these deployments end to end. This hits twice. Customers cannot maintain what they buy, and system integrators cannot scale delivery teams fast enough to take on more projects. I see this constraint directly in how far my own SI partners can stretch their capacity.

We have become excellent at pilots and mediocre at scale. I have written about this before, going back years: many organizations in Malaysia are still exploring what IoT can do rather than actually implementing it at scale. Government and GLC procurement cycles routinely stretch 12 to 24 months, and by the time a tender closes, the internal champion who pushed for the pilot has often moved to a different role. The institutional memory that would carry a pilot into a fleet-wide rollout simply evaporates.

5G hype outran 5G reality, and it dented confidence broadly. This one deserves more attention than it gets. 5G speeds actually fell 46% as user numbers scaled during 2024 and 2025, with real-world performance landing at roughly half of what marketing promised. Enterprise deployments involving sensors and remote machinery hit ceiling effects faster than expected. The irony is that most industrial IoT use cases never needed 5G in the first place. NB-IoT, LoRaWAN, and plain 4G cover the majority of real deployments. But 5G dominated the boardroom conversation for two years, and when it underdelivered, some of that disappointment bled into skepticism about connected technology in general.

Security fear has outpaced security literacy. IoT devices expand the attack surface for cybercriminals, and data privacy regulations around data ownership add another layer of complexity. Malaysia’s breach history has not helped confidence here. 2023 recorded the highest number of data breaches on record, with fifteen ransomware cases reported per week. For risk-averse government agencies and GLCs, “where does my data actually sit” has become a conversation-ending question, and few local vendors carry the certifications to answer it with authority.

Policy attention has moved on to AI, and IoT lost its dedicated spotlight. Look at where Budget 2026 puts its weight. RM53 million for the Malaysia Digital Acceleration Grant targeting blockchain, AI, and quantum computing. RM18.1 million for the National AI Office. RM2 billion earmarked for a Sovereign AI Cloud. IoT is barely named as a standalone priority anymore. Compare that to Budget 2025’s allocation of just RM15.1 million for smart city development under the Housing and Local Government Ministry, a rounding error next to the AI figures. Without a dedicated policy push, and without a compliance mandate the way India’s FASTag requirement forced RFID adoption almost overnight, Malaysian IoT adoption stays voluntary. Voluntary adoption is slow adoption by definition.

The Pattern Underneath The Pattern

Put these seven factors together and a single story emerges. Malaysia does not have a technology problem. It has a demand-side maturity problem sitting on top of a fragmented supply side. The billions poured into 5G, fiber, and data centers were supply-push investments, and they worked. The AI Nation agenda is also supply-push. What never got properly addressed is demand-pull: regulatory mandates that force adoption where voluntary uptake has failed, financing instruments that convert IoT capex into manageable opex, and system integrator capacity that can deliver at the scale procurement teams keep promising.

Where This Actually Gets Interesting

Here is the part I think most people in the industry are missing, and it is the reason I am not pessimistic about where this goes next.

AI cannot function in the physical world without sensor data. Every company now scrambling to bolt AI onto their operations is going to discover, within the next year or two, that they have nothing meaningful to feed their models. You cannot build a predictive maintenance AI without machine telemetry. You cannot build a smart agriculture AI without soil and climate sensors. You cannot build a smart building AI without occupancy and energy data. The instrumentation layer that IoT was supposed to build over the last decade is exactly the layer AI needs and mostly does not have.

Malaysia spent ten years underinvesting in that instrumentation layer relative to its own roadmap. That is the bad news. The good news is that the correction is coming, driven not by an IoT mandate but by AI ambition that will hit a wall without sensor data behind it. Companies that quietly kept building connected infrastructure through this slow period, the ones who treated IoT as the unglamorous plumbing rather than the headline act, are positioned to become the data supply chain for Malaysia’s AI Nation agenda.

That is not a consolation prize. That is the actual opportunity. The market did not fail. It just took longer to arrive at the reason it needed to exist.

Malaysia’s IoT-specific market figures vary considerably across research houses, and several published reports use templated methodology that should be treated with caution. The directional pattern across every credible source, however, is consistent: infrastructure has outpaced adoption, SMEs remain the binding constraint, and enterprise pilots are not converting to scale at the rate the roadmap assumed.

Mastering IoT & AIoT with FAVORIOT – eBook [Download]

Mastering IoT & AIoT with FAVORIOT — Free eBook by Dr. Mazlan Abbas
Dr. Mazlan Abbas · FAVORIOT
A Field Guide for IoT & AIoT Builders

From First Sensor
to Systems That Matter.

In Mastering IoT & AIoT with Favoriot, Dr. Mazlan Abbas walks you through a ten-act journey — the same one every IoT builder lives through — from that first spark of curiosity to deployments that actually change how decisions get made.

🔥 Free download — pay what you want, starting at $0

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PDF · Instant access — no experience required. Written for builders, not just engineers.

Mastering IoT & AIoT with Favoriot — book cover
The Problem

Most IoT projects never make it past the demo.

Not because the technology fails — because the thinking behind it does. This book was written to close that gap.

01

Cool demos, no outcomes

Dashboards get built, sensors get connected — and nothing downstream ever changes. Data is collected, but never acted upon.

02

The wrong starting point

Teams start with the technology instead of the decision it’s meant to inform, and the project drifts before it ever ships.

03

No practical path forward

Most resources are either too academic or too vendor-specific. What’s missing is a field-tested method to go from idea to working system.

Inside the Book

A ten-act journey, shaped by real deployments.

Told through relatable, real-world scenarios — smart vehicles, environmental monitoring, cold-chain tracking, and smart city systems — this book mirrors the actual path every IoT builder walks, following the Build-Readiness Ladder:

Cloud→ Dashboard→ Intelligence→ Decisions→ AIoT
The Starting Point

Why most IoT projects fail

Before you build anything, you’ll learn to recognize the common failure patterns that quietly derail IoT projects long before launch.

The Shift

From “cool demos” to measurable outcomes

A reframing of what success actually looks like — moving away from proof-of-concept theatre and toward systems that deliver decisions.

The Method

Idea to working system in four weeks

A practical, repeatable method focused on the part that matters most: turning raw data into decisions people can act on.

The Proof

Real scenarios across real industries

Smart vehicles, environmental monitoring, cold-chain tracking, and smart city systems show how IoT and AIoT come together in practice.

The Mindset

Why technology alone is never enough

The book’s central challenge: connecting the dots between sensors, data, people, and decisions — because dashboards don’t create value, actions do.

Who This Book Speaks To

Written for every role in the ecosystem.

Whether you’re just starting out or already delivering IoT for clients, the method holds.

St

Students

Building your first IoT project and want a real method, not just theory.

Lc

Lecturers

Shaping the next generation of IoT talent with field-tested material.

SI

System Integrators

Delivering solutions to clients and needing a sharper delivery framework.

Bz

Business Leaders

Seeking clarity on where IoT and AIoT actually create business value.

“If you’ve ever wondered what to build next — this book will show you where to begin, and how to go all the way.”

— Dr. Mazlan Abbas, Author
About the Author
Dr. Mazlan Abbas

Dr. Mazlan Abbas

Dr. Mazlan Abbas is the co-founder and CEO of FAVORIOT, a cloud-based IoT platform company with a partner network spanning Malaysia, Canada, Indonesia, the Philippines, and India. He previously served as CEO of REDtone IoT and Senior Director at MIMOS Berhad, with earlier experience at CELCOM Axiata.

He is Deputy Chairman of the Malaysia IoT Association (MIoTA) and a widely recognized voice in IoT and smart cities — a field guide written from inside the deployments, not from the sidelines.

Personal Voice Thought Leader Voice Travelog (Malay)
Limited Time · Free PDF

Stop waiting. Start building the system that turns data into decisions.

Download your free copy of Mastering IoT & AIoT with Favoriot today — no strings attached.

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Questions

Before you download

Is the book really free?

Yes. It’s offered on a pay-what-you-want basis starting at $0 through Payhip — you can download it at no cost.

What format is the book in?

You’ll receive a PDF file you can read on any device, immediately after downloading.

Do I need a technical background?

No. The book is written in a clear, story-driven style for students, lecturers, system integrators, and business leaders alike — not just engineers.

What will I actually be able to do after reading it?

You’ll understand why most IoT projects stall, and you’ll have a practical method for moving from idea to a working system in four weeks — with a focus on decisions, not just dashboards.

Why IoT Pilots Don’t Scale And Who’s Really to Blame

Everyone celebrates a successful IoT pilot. Nobody talks about what happens six months later. Here is an honest look at why IoT pilots fail to scale, and what both vendors and organisations need to do differently.

Everyone celebrates a successful IoT pilot. Nobody talks about what happens six months later.

I have been in this industry long enough to see the pattern repeat itself more times than I care to count. The pilot runs well. The demo impresses the right people. The case study gets written. And then, quietly, the project stalls. The vendor stops getting replies. The internal champion gets moved to another role. The budget for the next phase never quite materialises. Eventually, everyone agrees to revisit it next year, and next year never comes.

This is not a rare failure. It is, in many ways, the default outcome for IoT pilots. And I think it is worth being honest about why.

Pilots Are Designed to Win, Not to Grow

When a vendor runs an IoT pilot, the primary goal is to prove the technology works. Can the sensors communicate reliably? Can the data reach the cloud? Can the dashboard tell a compelling story? These are the questions that get asked, and they are the questions that pilots are built to answer.

What almost never gets asked at the pilot stage is this: what will it actually take to run this at ten times the scale, across three different departments, with an operations team that had no involvement in the original project?

That question feels premature when everyone is still excited about the demo. But it is the question that determines whether a pilot ever becomes infrastructure.

I went through this at FAVORIOT in our earlier years. We were focused on showing what the technology could do, and we were good at it. The pilots looked great. The clients were satisfied. And then the scaling conversation would arrive, and suddenly the gaps that were invisible at pilot scale became very visible. We had not asked the hard questions early enough, and neither had our clients.

The Organisation That Was Not Ready

I want to be fair here, because this is not only a vendor problem.

Many organisations that commission IoT pilots are not genuinely ready to scale the outcome, even when the pilot succeeds technically. They have not decided who will own the system once it moves from pilot to operations. They have not resolved the internal politics between the IT department, the operational team, and the business unit that originated the idea. They have not secured a realistic budget for scaling, only for testing.

Scaling IoT is not primarily a technology challenge. It is an organisational one. It requires data governance policies that most organisations have not written. It requires integration with legacy systems that were never designed to communicate with modern IoT platforms. It requires someone inside the organisation who understands the technology well enough to advocate for it internally, troubleshoot it practically, and keep it alive through the natural turbulence of business priorities shifting.

That person, the internal champion who bridges technology and organisational reality, is often absent at the start. And no pilot result, however impressive, can substitute for what that person provides.

Looking back at the IoT deployments I have seen actually scale, that champion is almost always present. They pushed for budget when enthusiasm faded. They translated technical requirements into business language. They trained colleagues who were sceptical or confused. Without that internal force, a successful pilot becomes a beautiful proof-of-concept that everyone agrees was interesting but no one quite knows how to build on.

The Vendor’s Honest Share

I am a vendor. I run an IoT platform company. So I say this knowing it applies to me.

The commercial pressure on IoT vendors is to win the pilot. The incentives are structured around closing deals, not around ensuring clients succeed eighteen months after the handover. Sales teams make promises during the pitch that reflect best-case conditions. The pilot is then designed around those best-case conditions. When the client tries to scale into their actual messy environment, with their legacy systems, their budget constraints, and their internal disagreements, the gap between what was promised and what is possible becomes apparent.

Beyond the sales process, there is a deeper structural problem. Many IoT vendors invest heavily in customer acquisition and very little in customer success. Helping a client scale is slower, more complex, and less commercially visible than winning the next pilot. The skills required are different too. You need to understand the client’s internal culture, their risk tolerance, their pace of decision-making. Most vendor organisations are not built for that kind of long-term partnership.

What Scaling Actually Needs

If you have just completed a successful IoT pilot and you are serious about scaling it, here is where I would start.

Ask the governance questions before the growth questions. Who owns this system? Who has access to the data, and under what conditions? Who is responsible for maintaining it when the original project team moves on? These conversations feel administrative, but they are what determine whether the investment survives contact with the organisation over time.

Make sure the technology was chosen with operations in mind, not just with the demo in mind. A highly customised pilot solution that runs beautifully in a controlled environment can become extremely difficult to hand over to an operations team that was not involved in building it. Standardisation, supportability, and documentation matter far more at scale than they do at proof-of-concept.

Build internal capability alongside vendor engagement. The organisations that scale IoT well treat adoption as a learning process, not just a procurement process. They develop expertise inside the team. They make sure the knowledge does not leave when the vendor’s project engagement ends.

And if you are a vendor reading this, I would gently suggest reexamining what success actually means for your business. If your client’s pilot succeeds but their deployment never scales, did you really deliver value? The answer is uncomfortable, but it is worth sitting with.

The Blame Is Shared, and So Is the Solution

The reason IoT pilots fail to scale is rarely a single failure. It is usually a combination of technology choices made under pressure, organisational readiness that was overstated, vendor promises that outran execution capacity, and a structural mismatch between how pilots are designed and what scaling genuinely demands.

That is both a frustrating and a hopeful conclusion. Frustrating because there is no single villain to point at. Hopeful because it means there are multiple places where both sides can make better decisions.

I have seen IoT deployments that started small and grew into something that genuinely changed how an organisation operates. Those projects did not succeed because the technology was exceptional. They succeeded because both sides were honest about the challenges, patient with the timeline, and committed to the outcome long after the first demo had faded from memory.

So here is the question I want to leave with you: if you have been through an IoT pilot that succeeded technically but never scaled, what was the one thing you wish both sides had discussed more honestly at the very beginning?

If you’re working through this challenge right now, I’d also point you to what we’ve been building at Favoriot — specifically around helping organisations move from pilot to operational deployment without rebuilding from scratch.

Why Blogging When Nobody Was Reading Was the Best Business Decision I Ever Made

The long game of content, before it was called content marketing. How years of blogging to an empty room became the foundation of a business, a reputation, and a life’s work in IoT.

Let me ask you something. If you wrote something today and nobody read it, would you write again tomorrow?

Most people would say no. And I understand why. We live in a world that measures everything in likes, shares, reach and impressions. If the numbers don’t move, the assumption is that nothing is working. That you are wasting your time. That maybe you should stop.

I started blogging around 2009. At that time, IoT was barely a word in people’s vocabulary. Social media was young. And I was writing about telemetry, machine-to-machine communication, and connected devices… to what felt like an empty room. The analytics were humble, to put it kindly. Sometimes a few dozen readers a day. Sometimes less.

But here is what I know now that I didn’t fully appreciate then: that empty room was being recorded.

Planting Seeds Before Anyone Was Hungry

When I wrote in those early years, I wasn’t writing to go viral. I was writing because I had ideas that needed to get out of my head and onto paper. I was processing things I had seen in my career at MIMOS, CELCOM and UTM. I was trying to make sense of where technology was heading, and writing was how I thought through things properly.

There was no content calendar. No SEO strategy. No analytics dashboard I checked obsessively every morning. Just me, a laptop, and the belief that what I was writing about actually mattered, even if the world hadn’t caught up yet.

And then IoT exploded.

Between 2013 and 2015, the conversation around connected devices went from niche to mainstream almost overnight. And suddenly, people were looking for someone who understood the space, someone who had been thinking about it, writing about it, for years. That someone was already there. I had the archive. I had the track record. I had the voice.

That is when I understood what I had been doing all along. I had been building credibility on a platform I owned, quietly, consistently, before there was any social pressure to perform.

The Business That Content Built

When I co-founded FAVORIOT in 2017, I didn’t have to start from zero when it came to reputation. The blog had done years of work. Every article I had written about IoT platforms, smart city infrastructure, the challenges of data connectivity… those were bread crumbs that led people to me long before FAVORIOT existed as a company.

Investors ask you what makes you credible in your space. Customers ask why they should trust you over a larger competitor. Journalists ask why your opinion matters. What I could always point to was the body of work. Not a pitch deck, not a fancy website, but hundreds of posts that showed how I thought, what I believed, and how long I had been in this conversation.

You cannot fake a ten-year archive of consistent ideas.

That is what content does when you treat it seriously over a long period of time. It becomes proof. It becomes your reputation, made searchable and permanent.

When Nobody Is Watching, That Is the Real Test

I want to be honest about something. There were stretches of time when I wondered if I should just stop. The numbers were not rewarding. Nobody was sharing my posts to their thousands of followers. The inbox was quiet.

But I kept asking myself: do I believe what I am writing? Do I think this matters?

The answer was always yes. And that is what kept me going.

Looking back, I think the discipline of writing when nobody was watching was actually what built the quality of my thinking. When you write for an audience that doesn’t exist yet, you can’t rely on trending topics or viral hooks. You have to write something true. You have to be genuinely useful. You have to develop a real point of view, because there’s no performance to hide behind.

That pressure, the pressure of honesty over popularity, sharpened me in ways that no conference or workshop ever could.

The Compound Interest of Ideas

There is a concept in finance called compound interest. Money grows not just from what you put in, but from the returns building on themselves over time. Content works exactly the same way.

A post I wrote in 2011 about sensor networks brought me a speaking invitation in 2014. A talk in 2014 turned into a collaboration in 2016. A collaboration in 2016 led to a client for FAVORIOT in 2019. And so on. The chain of connections is rarely obvious when you are in the middle of it. You only see it clearly when you look backwards.

If I had stopped blogging in 2010 because the numbers were small, none of those downstream opportunities would have existed. The compound interest would never have started accumulating.

This is what people miss when they treat content as a short-term campaign. Content is infrastructure. You build it slowly, you maintain it, and it works for you even when you are sleeping, traveling, or running a startup that demands every hour of your attention.

What I Tell Founders and Professionals Who Ask Me About Content

People often ask me: “Mazlan, should I start a blog? Should I write on LinkedIn? Is it worth it?”

My answer is always the same. Ask yourself not whether anyone will read it today, but whether you believe what you are writing is true and useful. If yes, write it. Then write it again next week. And the week after that.

Stop thinking about content as a marketing activity. Start thinking about it as a thinking habit that happens to be public.

Because the day will come, and I genuinely believe this for anyone with real expertise and something honest to say, the day will come when someone will find that old post you wrote when nobody was looking, and it will open a door you never expected.

I have lived that story more times than I can count. And it all started with a decision to write anyway, even when the room was empty.

So let me leave you with this: what do you know right now, in your field, in your experience, that the world hasn’t fully caught up to yet? Are you writing it down? Are you sharing it?

Because someone out there is about to start searching for exactly what you already know.

Why I Want More Malaysian Students to Brag About Their Projects

Malaysian students build impressive projects but rarely share them publicly. Here is why that needs to change, and what students, lecturers, and institutions can do about it.

Have you ever built something and then kept it to yourself?

I have seen this happen too many times, and it bothers me more than I probably let on. A student spends weeks getting an IoT sensor to talk to a cloud platform, wires everything up, writes the code, stays up late debugging, and then… nothing. They submit the assignment, get their marks, and move on. Nobody outside that classroom ever knows the project existed.

That project deserved better. And honestly, so did the student.

The Culture of Hiding Our Work

I think we have a cultural habit in Malaysia of downplaying what we build. We are taught, from a young age, that showing off is rude. That humility means staying quiet. That if your work is good, people will somehow find out on their own.

But in the world we are living in today, that thinking is holding our students back.

I recently wrote about how some students in Malaysia are still learning IoT using Blynk, ThingSpeak or Favoriot, platforms that have genuinely served the community well over the years. My concern was not with the tools themselves, it was with the possibility that some students might complete their programmes without being exposed to more current, industry-relevant environments. The response to that piece was warm and it opened a much bigger conversation I want to continue here.

Because there is a second problem, and it sits right next to the tools issue. Even when students build something impressive, they rarely tell the world about it.

What “Bragging” Really Means

I want to be careful with my word choice here, because when I say I want Malaysian students to brag, I do not mean arrogance. I mean documentation. I mean visibility. I mean the courage to say, “I built this, and here is how I did it.”

In the global tech community, sharing your work is not showing off. It is how you contribute. It is how you invite feedback, attract collaborators, and build a reputation before you even graduate. Every time a developer writes a blog post about what they learned building a project, every time a student posts a short video demo on LinkedIn or YouTube, every time someone publishes their code on GitHub with a clear README, they are adding value to the community.

They are also building something that a CV alone cannot carry: a visible portfolio of thinking.

I Have Seen What Happens When Students Share

When students do step forward and share their work, remarkable things happen. I have seen students connect with mentors because someone stumbled across their blog. I have seen project ideas get picked up by companies that were looking for exactly that kind of solution. I have seen young engineers get job offers because a hiring manager found their GitHub repository.

And I have seen something perhaps more important: the student’s own confidence change. When you write about your project publicly, you are forced to explain it clearly. You start to understand what you actually built. You start to see what worked and, more importantly, what did not. That reflection is part of the learning that never shows up in an exam.

The Platforms Are Already There

There is no shortage of places where Malaysian students can share their work. LinkedIn is the obvious starting point, and yet I still see so many profiles with nothing more than a degree listing and a generic summary. Imagine if every final year IoT project at a Malaysian university had a proper LinkedIn post, with photos, a short explanation of the problem it solved, and the tech stack used.

GitHub is equally powerful. A well-documented repository says more about an engineer’s capability than almost anything else. Medium or WordPress and personal blogs remain excellent homes for longer technical write-ups. YouTube or TikTok are perfect for demo videos. Even short-form platforms have an audience hungry for genuine student work.

The tools to publish are free. The audiences are there. What is missing is the habit and the encouragement.

What Lecturers and Institutions Can Do

I want to be fair here: this is not entirely on the students. If we want a culture shift, we need to start from inside the institutions.

Imagine if project documentation and public sharing were built into assessment rubrics. Imagine if a student was graded not only on whether the sensor collected data correctly but also on whether they could explain the project clearly to a non-technical audience. Imagine if universities celebrated student projects the way they celebrate sports achievements.

Some institutions are already doing this, and I applaud them. But it needs to be more systematic. Students should graduate not just with technical skills but with the confidence and habit of communicating those skills to the world.

A Personal Challenge

If you are a student reading this, I want you to do one thing this week. Pick a project you are working on or have completed. Write about it somewhere public. It does not have to be perfect. It does not have to be long. Just write honestly about what you were trying to solve, what you used to solve it, and what you learned in the process.

That one post could be the start of something you cannot predict yet.

If you are a lecturer or a programme coordinator, think about how you can make sharing a formal part of the learning journey. Not as a burden, but as a skill that students will use for the rest of their careers.

Malaysia has genuinely talented engineering students. I have met many of them, worked alongside some of them, and been impressed by what they can build when given the space to do it. My concern is that too much of that talent is invisible to the industry because no one taught them that visibility is part of the job.

So tell me, if you could make one change to how Malaysian engineering education celebrates student work, what would it be?