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Challenges of Integrating Legacy Systems with IoT Solutions

Challenges of Integrating Legacy Systems with IoT solutions. Business Challenges with Legacy-IoT integration. Technology Challenges with legacy IoT integration.

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Business Challenges with Legacy-IoT integration

We are rapidly moving from a disconnected world to a hyperconnected one. From smart homes to smart cars, everything reflects how much effort is being put behind crafting products and services that bring hyper-connectivity to us.

With new products and new services, it is much easier to deliver connectivity. But, what about existing devices and services that require connectivity?

Given that more than 85% of all devices are legacy, it brings a huge challenge to the growth and adoption of IoT solutions. Also, note that most of the legacy systems in industrial usage come with a lifespan of 10 years or more.

Challenges of Integrating Legacy Systems with IoT solutions

And it isn’t easy to replace those devices. Replacing them comes with a high cost, which is neither feasible for consumer IoT nor industrial IoT scenarios.

With this blog post, we are going to show some of the most common challenges of integrating IoT solutions with legacy systems.

A. Business Challenges with Legacy-IoT integration

If you are planning to get started with a legacy-IoT integration project, here are the top five challenges enterprises usually face:

  • Complex business analysis with a lack of subject matter experts
  • First mover’s disadvantage – a common threat to legacy IoT integration projects
  • Lack of tech talent to carry out complex integration
  • Keeping cost controls in check
  • Constant flux, rapidly evolving technology landscape

Let us walk you through those five business challenges in some more detail.

1. Complex Business Analysis

From user research to project scoping, business analysis is a big challenge to your legacy integration project. It requires you and your team to carefully put together and analyze challenges, opportunities, and potential innovations.

Apart from business analysis being too hard for such initiatives, if you fail during this first crucial step – the entire project is exposed to the risk of failure.

2. First Mover’s Disadvantage

Unlike most software engineering projects, IoT is a space where being the first mover is often a disadvantage. Imagine being the first mover where not only hardware, cloud, front-end, and APIs are a challenge – but also the risk of working on integrating a legacy Visual Basic based system is at a whole new level.

3. Lack of Tech Talent

Think about it, how many professionals around you can port legacy hardware architectures to an evergreen one? Or, how many professionals have the skills to drive development and integration of a modular gateway predictably?

The answer is a handful. That’s what makes it so challenging to assemble the right team that can drive the project to success.

4. Controlling costs and managing the ever-evolving landscape of IoT

Given the first three obstructions, it is rather easy for you to see why controlling costs can be a big challenge. And the fact that IoT keeps evolving makes it much harder. Let us illustrate that to you with the case of Lora.

For example, it was only 5-6 years ago when LoRa didn’t seem like a protocol that would receive such wide adoption. Businesses at that time were forced to adopt SDR. Implementing SDRs bring 100x more cost to an enterprise than what LoRa does. Those that invested in LoRa as opposed to SDRs now reap the benefits of having a competitive edge.

Now that you know what obstacles you’ll have to deal with while integrating legacy systems with IoT solutions let’s get into technical challenges.

Technology Challenges with legacy IoT integration

B. Technology Challenges with legacy IoT integration

Data and Infrastructure Challenges

There are three main challenges in heritage IoT integration when it comes to data:

  • Implementing data security – Identity management and secure authentication
  • Data architecture to ensure data integrity across hardware, middleware and cloud
  • Local networks to support data transport

Most legacy devices weren’t initially built with security in mind. And, they commonly push raw data through legacy connectors like RS232. A lot of legacy medical equipment comes with ports like RS232, and the data lacks any form of encryption.

Most of these devices (e.g., an EEG machine) were designed to push information to a monitor. When you match baud rates and pull serial data from those legacy devices, it is up to your IoT devices/network to encrypt this data and push EEG information forward. This puts a lot of weight on your IoT devices, which often don’t even have a microprocessor.

The next challenge is in setting up the right data infrastructure.

Legacy equipment pushes a lot of data, and everything right from your data architecture, APIs to your network reliability should match to deliver to these expectations. This means that your entire data architecture should be built to serve data transport requirements that support security, integrity, scale, and high velocity.

1. Legacy IoT Deployment and Management

A successful IoT legacy integration project requires a vision that not only crafts a technically perfect product but also thinks about how you will manage and support it throughout its lifetime.

Deployment and management are those spaces that you have to put together, analyze rigorously, and innovate upon. While manual inspection and upkeep are always an option, automated deployments are the key to highly maintainable and scalable IoT legacy integrations.

2. Communication standards in legacy systems

When you think about communication standards in legacy systems, there’s a lot to think about. Legacy systems evolved with communication standards that initially weren’t designed to support connectivity and innovation.

Given that most of these standards were proprietary innovating on top of these protocols is not an easy task.

That’s precisely where the choices to set up system architecture, and select technology stack are most important. For example, if you are planning to integrate an IoT solution with a manufacturing system, selecting a language or framework that supports an OPC based communication system makes all the difference.

.NET, for example, not only makes it easy to integrate IoT solutions with OPC systems, but the evolved version .NET core also takes it a step further. While making it incredibly intuitive for system integrators to work with OPC based legacy systems, it also brings along powerful data processing and AI capabilities

3. Quality Control over legacy IoT integration projects

From integrating legacy to building/integrating IoT networks – quality control determines how far your plan will go. Apart from the usual hardware and software quality control challenges, legacy IoT exposes your projects to the risks of facing edge cases that are very difficult to explore during the early test stages.

Having the right experience and the right set of talent is the key to effectively exercising quality control over your projects.

And that’s it!

Tackle those challenges right from the start, and you always reach SLAs and expectations that you set with legacy IoT Integration projects.

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Automotive

How MEMS Mirrors can make LiDAR Economical

All of this was made possible via MEMS mirrors. Do you know how they can assist in lowering the cost of LiDAR?

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7 Latest Tech Automobile Advancements

LiDAR is a complex technology that has gone through many adjustments and upgrades before becoming efficient and accessible for an average consumer. The bulky and expensive LiDAR has been dramatically improved as a consequence of continuous improvement. All of this was made possible via MEMS mirrors. Do you know how they can assist in lowering the cost of LiDAR?

While LiDAR systems struggled with its fundamental problems such as high cost, big size, limited edition, and low efficiency, technology has found a solution in the form of a MEMS scanning mirror.

1. What is LiDAR?

LiDAR is a light and range sensor or laser projection with distance detection. They became trendy after introducing the first uncrewed vehicles; for example, in uncrewed Yandex automobiles, the LiDAR sensor aids in orienting the vehicle in space.

The term LiDAR refers to the use of light to track the position of objects on a plane. The technology was developed in the 1960s. It was initially designed to track satellites and military targets. Later on, technology permeated other aspects of human life.

2. Key Challenges of LiDAR

Any technology sooner or later starts experiencing difficulties. LiDAR is no exception. Although, in theory, everything seems to be ideal, the reality shows that LiDAR struggles with the following issues, which limit its ability to be widely used and make it expensive:

Automated headlight control

  • It needs a mechanical mirror to deflect the laser beam;
  • Mandatory use of motor for rotation of mirror about its axis;
  • The engine consumes a significant amount of power;
  • The machine is substantial.
  • The high cost of mirrors;
  • Such an extensive system is frequently heavy and can only be integrated into large applications;
  • Many LiDAR applications necessitate a wide field of view.

3. What Are MEMS Mirrors?

MEMS (Micro-Electro-Mechanical Systems) are mechanical structures that can be miniaturized and fully integrated with electrical circuits. These microscopic electromechanical components can perform computational and communication functions while consuming very little power and tiny size.

4. Does LiDAR Work With Mirrors?

LiDAR sensors based on MEMS mirrors are a promising solution. MEMS mirrors have a well-developed silicon design that has proven to be effective in various automotive applications.

MEMS mirrors have many advantages for LiDAR, including:

No need for rotating components. As a result, the MEMS-based LiDAR system is more robust and more durable than the mechanical LiDAR system;

  • Market accessibility;
  • Compactness;
  • Small deflection angles.

A team of researchers from the University of Florida developed a prototype of the LiDAR system using the property of MEMS mirrors to deflect the laser. Not only does the novelty have a wide field of view, but it also consumes very little power. Moreover, due to its small size, it can be easily mounted in small applications.

In the LiDAR system, this feature of MEMS mirrors is used as a scanning element. As a result, the LiDAR device can be powered by a 9V battery charge. The LiDAR prototype also includes an infrared sensor, which is activated only when specific parameters are met.

The prototype has a simple design, but it is one of the bulkiest and energy-intensive components of LiDAR systems. As a result, it is ideal for residential and commercial applications that use intelligent environmental control systems. The developer team plans to improve the LiDAR system by reducing its size and power consumption.

The smaller volume and lower cost of the LiDAR will aid in its integration into a wide range of applications, such as various sensors and control systems that can display the immediate environment. We anticipate that consumer interest in future LiDAR based on MEMS scanning mirrors will increase.

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