Steps to Build Your IoT Prototype

The Internet of Things or IoT has taken over every major facet of our lives. From research labs, the path-breaking technology has moved out and found a place in our homes, kitchens, offices, gardens, and roads. 

Shortly, connected devices are poised to become more accessible and affordable than ever before. Needless to say, their demand is going to surpass all limits, and businesses dealing in the niche can literally mint money riding the wave. So, if you haven’t yet jumped on to the IoT bandwagon, now’s a good time to do so and understand how this disruptive technology works.

Just like all software solutions, IoT projects also start with prototyping. Your IoT prototype outlines all the required parameters of your IoT deployment. It binds together all the elements of your project- device, user, cloud, and enterprise. But creating a perfect prototype is easier said than done.

In this post, we will be discussing the main steps involved in IoT prototyping. But first, let’s understand how IoT prototyping is challenging.

How Is IoT Prototyping Unique and Challenging?

Prototyping for an IoT product will be different than for other software. When your team first forays into IoT, here are some things they might find disconcerting:

The prototype will not be production-ready: When you prototype for non-IoT solutions, whatever you include in their prototypes reflect in the final products as well. This is not the same with IoT products. The hardware and software in their prototypes and final products may vary widely. Moreover, there are many third-party integrations that are not included in prototypes.

Few ready-to-use components: Unlike other software prototypes, IoT ones don’t have the advantage of readymade components. Your development team will have to start from scratch, building components one by one. Feedback and testing cycles will be longer and usage instructions will need to be more in-depth since users are not very familiar with connected devices as yet.

Software occupies center-stage: IoT hardware takes time to master. But if your software facilitates user onboarding, the user experience can be seamless and smooth. In order to overcome friction, IoT prototypes need to lay special emphasis on user experience.

Products should be high on usability: Sticking a chip into a device and connecting to the web does not comprise IoT. A real IoT product delivers value from the get-go, even if it doesn’t look too pretty. It is made after tracking consumer behavior and action. It doesn’t overpromise and underdeliver, rather vice versa.

5 Steps to Create Your First IoT Prototype

Building your first IoT prototype can be challenging and exciting at the same time. A typical prototyping process consists of four major stages. Let’s take a deeper look at them.

Stage 1: Identify the Goals of Your IoT Prototype

When prototyping an IoT product, it’s essential to drill down into its objectives first. 

For instance, if you anticipate glitches in how your device will interact with real users, tackle that first. Keep it at the focal point of your development process and plan your hardware, software, and other requirements around it.

Ask yourself questions like:

  • What will the IoT prototype achieve?
  • What kinds of data do you need to capture for the prototype?
  • Where will the captured data be logged?
  • Where will you put all the UI elements (wireframing)?
  • What kind of discussions do you want to have with your developer teams?

By keeping your end goals in sight, your project will get direction and momentum. Plus, it makes sense to work on these assumptions right away rather than when you’re well into the process and down thousands of dollars already.

Stage 2: Research on IoT Hardware and Components

Once you have identified the pain points that your product will address, it’s time to dig into the hardware components and technologies that will help you achieve the end goal. 

Hardware for prototyping will be very different from production hardware. 

How, you wonder?

Prototyping hardware will be:

  • Flexible: It will be breadboard-friendly.
  • Affordable: It will be low-cost.
  • Modular: It will be compatible with multiple hardware ecosystems.
  • Usable: It can be set up in a short time and comes with built-in tools.
  • Simplistic: It can easily be used by beginners.

As against this, production hardware is more reliable, manufacture-ready, and advanced.

While deciding on your IoT prototype’s hardware, find answers to questions like:

  • Does the hardware have a consistent firmware, platform, infrastructure, and development tools?
  • Is there sufficient resources and domain support around your chosen hardware?
  • How easy are the components to deploy? Can you get your prototype up and running with the components or do you have to go hunting for installation guides and experts?

Be aware that there is a lot of experimentation involved in this step of hardware selection. 

It’s likely that you will create a solution, test it, and end up scrapping it multiple times. Sometimes, it might seem akin to searching for a needle in a haystack, but pursue till you zero into the perfect strategies for your product.

For example, if your IoT product is Bluetooth-based and requires many connections to transfer data simultaneously, you may need to experiment with different Bluetooth devices to find the best connection. 

Front-end and backend functionalities may need to be synced over and over again through different technologies until everything works in tandem. If you give up after a few fails in the initial stages, you may never find your ideal technology and solution.

Stage 3: Design and Acquire the IoT Components

And now, we come to the most exciting stage of prototyping – product creation. We recommend that you start building early so as to spot discrepancies and fix bugs without affecting your delivery schedule. 

There are four basic components of an IoT prototype:

  1. Devices/Sensors 

Sensors and devices collect data from the product’s surroundings. These sensors come in varying degrees of complexity- from basic temperature monitors to complicated video feeds. You need to either acquire or design your own sensors for your IoT product.

  1. Connectivity

There needs to be a channel for the senor-collected data to be transported to the cloud infrastructure of IoT devices. These networks can be cellular, satellite, Bluetooth, WiFi, Wide Area Networks (WAN), or any other type. Whatever be your network choice, ensure that it is leakproof and secure.

  1. Data Processor

Once data reaches the cloud, it needs to be processed to generate some output. The data processing can range from simple (checking temperature range on your smart AC) to complex (scanning the area for unknown intruders). 

Sometimes, the user’s intervention is required for the data processing to complete. That’s where the next IoT component, user interface, comes into the picture.

  1. User Interface

There needs to be an interface through which users can interact with the IoT system. The user interface, users can check into their devices, provide inputs, and extract output. The UI can be a simple touch screen or a complex video feed, depending on the device and requirements.

While designing/acquiring IoT components, keep your end goals in sight. Ensure that the hardware and software components are compatible with each other. During the prototyping, it’s okay to encounter some glitches and failed iterations. Don’t lose heart and keep persevering until you have a full, working prototype in your hands.

Stage 4: Define Data Streams

To take advantage of the massive volumes of live data collected by your IoT device, you need to set up secure data streams. 

There are a number of caveats to defying data streams:

  1.  They should be secure and tamper-proof.
  2. They should be able to collect and tramt millions of data points simultaneously.
  3. They should be equipped to acquire, manipulate, collate, combine, and discard data as programmed.

One of the biggest challenges you’re likely to face is the distributed nature of data. Your data streams will have to collect and assimilate data from varied data sources – sensors, cloud, user interface, and others. 

If your data streams don’t configure data lineage accurately, data processing will take a hit. To do so, you can define data clusters using Apache frameworks. If your data streams are more complex, I recommend you use Kafka or Spark Streaming. 

Stage 5: Integrate with App

Integrating IoT with mobile apps is the last but most critical step of prototype development. Mobile IoT solutions can have unidirectional or bi-directional data transmission/communication between users and the device in question. Whatever be your development model, ensure that the integration is smooth and seamless.

IoT-powered smartphone apps can be of many kinds, ranging from wearable devices (like smartwatches and heat rate monitors), industrial plant monitors (to keep tabs on plant vitals), agro apps (to regulate irrigation rates, etc.) or traffic moderators (for decongesting traffic, assisted parking, etc.).

After you’ve got your IoT product up and running, the next step is to fix the bugs. These errors might be software-related like broken features or code issues, or hardware-related like patchy connectivity or skewed interface. 

Whatever the issues are, take the time to recode, retest, and eliminate each and every bug. Ensure the product holds up to scrutiny by experts and real users alike. If there is a flaw in the core design and coding, you may need to go back to the drawing board and start from scratch. 

Sounds overwhelming?

It can be. Coders and developers often like to share a joke that this stage typically called “the last 20%” ends up consuming 80% of the entire bandwidth. 

It’s fair to assume that unexpected twists will crop up during this troubleshooting stage. But since you’re so close to the final prototype, you need to keep the momentum going even if there are a few roadblocks. At the end, you should have a bug-free, full-featured prototype that meets its objectives.

Ready to Build Your IoT Prototype?

Prototyping is non-negotiable when it comes to IoT products. Clearly-defined goals, robust technologies, and rigorous testing can ease prototyping to a great degree. The approach described above can be your compass through the entire process.

Do you have any questions about IoT or prototyping? Leave them in the comments below. For more helpful and insightful information in this space, stay tuned in.

To know more about iView Labs, kindly log on to our website www.iviewlabs.com and to get in touch with us with your queries and needs just write us an email on info@iviewlabs.com and sales@iviewlabs.com.

Download the latest portfolio to see our work.

MWFM ( Mobile Work Force Management) Increasing field operations by 4X and bringing down cost to 6X on Human resources.

Code, Coffee and tracking 2m Users ..

How we helped our African friend to break the ice and board 2m Voters?

Tracking 2m+ voters and 3000+ agents

Day 2 at Hannover messe was a bright sunny day. I was gathering my thoughts and plans for the day, as we had couple of meetings and presentations lined up on this day. At sharp 11:30 AM I gave my presentation on HealthCare Product www.prapp.in (a platfrom for health engagement connecting patients to doctors). As soon as my presentation was over, there were some folks who were interested in doctor-patient engagement platform. There was absolutely no breather in between. I just grabbed my cup of coffee and headed towards my booth.

I observed that day 2 was a rush rush at Hannover. Lot of delegates from different countries were visiting the fair. Suddenly some African folks in a team of 3 dropped by at our booth and here starts our conversation:

Mr. Bamaba: is this Sid from iView Labs

me: yes , I hope you are doing great! How may I help you!

Mr. Bamaba: Do you do location tracking and mapping?

Me: Sir, I would like to hear the problem that you are facing..

Mr. Bamaba: We need to map all the voters of Africa on the map. We want to verify their identity and address. To do these we send agents on the field who do it manually and all these data gets centralized. Since its a manual process we were having lot of data issues and productivity. We are here looking to solve this issue

Me: Ok Sir, I understand your problem. So, what these agents would be carrying with them to verify the voter.

Mr. Bamaba: These agents will be carrying our assigned tablets for verification. Look we have 3000+ Agents who are in field of collection of the electoral census and here we need to observe their day to day actions as per the geographies they are moving. Can you develop me a platform where in I can see all these agents in real time? I have to catch the coordinates and want to see the efficiency and methods they are adopting to do this quick exercise. Also I want to assign the further tasks of Route Optimization

Me: In a nutshell, I was completely able to understand what my friend was looking to build. Me and My CTO was there and we explained him our methodology of working and strategy of building this solution.

After all the explanation, he seemed convinced to do business with us and finally we were able to strike the deal with our African friends.

As the project kicked off, my technical team started brainstorming about the project and came up with the complete technology stack and architecture for the project. For this solution, we knew the crux of the entire solution would be accurate position mapping, path tracking and real monitoring of agents. Also, the tricky part here was about offline position tracking due to network connectivity issue in small villages and data pruning as position mapping of each agent for each second would generate enormous data in the application.

With the technical risks identified, we started working on the project and were very thrilled to work on this as we saw that how this solution could be used for various industries who has a mobile force or field force. We realized the scalability and reusability of this project, hence we made this in a modular form where entire location tracking module is an independent module which could be rightly fitted into any industry.

We started working on day and night on this project to get this all right. We send our guys on the field to test in all various conditions such as speed variance, location variance etc.

Finally we were able to get all the systems in place and deliver it to our African friends.

The entire data of the application rests on AWS ( Amazon Web Services) cloud.

With our approach to take software development as the Lego and Brick Building job we were able to deliver this solution in span of 3 months.

With over 2 million Voters on Board of eCampaign and 3000+ agents on the admin side the eVoting, this was a huge success for our mobile workforce management solution.

Admin Panel( Operations Guys) for tracking the field force :-

08

Android App ( for the field force/Agents in the fields) : –

01

Here the entire Platform does the following job for the African government : –

1. Task management
2. Task allocation
3. Task control
4. Voters geography tracking
5. Agents tracking
6. Task completion
7. Real time visibility

Data analytics per Agent and Voters

Business benefit to our African friend:

  • 50+ Nos of Men power reduction by Using the eVoting eCampaign solutions.
  • Improvement in HR process to know the real productivity by real time tracking on faily field activities.
  • Cost savings to a multiple times and bringing in lean business.
  • Perfect tracking of census with error free data.

Is DATA the new energy?

I think we should stop looking at data in the form of petabytes, zettabytes etc rather we need to have a new perspective to look at data in the form of energy. An energy which is renewable in nature and can be used in multiple forms to serve more than one purpose. An energy can be generated from multiple sources such as sun, wind, geothermal, biomass etc. in the same manner Data energy can be created from multiple sources. Data in the raw form is of no use unless it is extracted, processed and refined to make it to use. In the similar manner we need to extract and process the energy to have its maximize use.

Data uncaptured, unprocessed is a loss of energy for businesses to build insights which can help them make sound decisions. The value of the data in a business keeps on growing with the new pieces of information added. Critical insights of the business can be drawn with the right technology in place to refine your data.

Energy storage is capture of energy produced at one time for use at a later time. This is so relevant and apt if we draw an analogy for the same in terms of data. Data is also captured at a given time to make it to use at a later stages. We need huge storages to store large amount of energy and same is the case is with data. These data storages are huge in terms of processing power to manage BIG DATA. Energy storage involves converting energy from forms that are difficult to store to more conveniently or economically storable forms. The question here how we can apply the same principle for data being stored? How we constantly churn raw data from these data storages into different meaningful forms.

Unlike other energies, the biggest advantage of Data is we don’t have to worry about its depletion, we only have to worry about its refinement and extraction with the desire to improve efficiencies and make informed decisions.

Of course, lot of analogies can be drawn between energy and data for us to handle our new digital age of IoT sensors. In every ecosystem, there is a main producer of the energy and there are different levels of consumers and producers which co-exist in the system. In the digital Age of sensors and devices, we need to make devices intelligent enough to coexist as a data consumer & producer to create a meaning out of the ecosystem.

We at iView Labs are constantly thriving to create that coexistence of data energy consumer & producer.

Time saving for Patient & Doctors to Search for Electronic Health Record

We are fast moving into a “Predict and Fix” model in the medical sector, and patient data plays a key role.

The biggest dilemma that the healthcare sector in India and the world is the digitization of patient records. With millions of megabytes of data being generated every day, this number is only going to grow in the next few years and we at iView want to make your Healthcare business ready for this boom.

Reducing human intervention and the subsequent error beckons the urgent need of digitalization. That’s where our innovation, the Prapp comes in.

The Prapp is a connected health system for small clinics as well as big networked hospitals.

The idea of the product stemmed from our market research in which the number one grouse the doctors had- was that a significant portion of the medical personnel’s time to dedicated to entering data concerning vital and patient history information. Automation of the data is the Prapp’s biggest USP. An interoperable hospital system which collects all vital patient data as soon as they walk in. How? Our engineering team along with data scientists focused on sensor technology to develop an IoT based platform for information on a patient’s weight, blood pressure, glucose levels etc. This data is automatically fed into a central system which is connected to the cloud for access anywhere, 24/7. Furthermore, the multi-platform supported doctor panel also allows for maintenance of appointments, medical records and it’s monitoring- even from a remote location.

Pattern recognition into a patient’s wellness will aid the doctor in giving prompt and correct diagnosis while also factoring in physiological changes and lifestyle. Prapp is an interoperable health information network aimed at reducing the gap in the doctor- patient relationship. It is highly customizable and can be broken down into individual solutions depending on varied needs.

We strongly believe in the potential and the revolution that IoT will bring to the world. We aim to connect businesses, patients, personnel and doctors into one framework and usher in the new age in healthcare.