How wonderful is it to come home after a hot summer's day and find your home is nice and cool simply because your thermostat and AC unit are part of an ecosystem that automatically manages your house? Here lies the beauty of the Internet of Things. From managing our homes to protecting our cars and monitoring our health, IoT has infused intelligence into our everyday objects, turning them into smart devices and creating a more connected, more efficient world for us all.   
 
What is IoT?

The Internet of Things, or IoT, is so much more than a buzzword or a cool tech term – it’s the collective network of devices that connect and exchange data with each other and the cloud, including the technology that facilitates their communication. According to McKinsey “The Internet of Things (IoT) describes physical objects embedded with sensors and actuators that communicate with computing systems via wired or wireless networks—allowing the physical world to be digitally monitored or even controlled.”  
 
A thing in IoT can be any type of device, like a heart monitor implant, a smart refrigerator, a car with built-in sensors, or any other object that can have an assigned IP address and can exchange data with other devices on the network. An ecosystem of smart devices embedded with software, connectivity, and sensors that collect, send, and act on data they acquire from their environments.  
 
Why is IoT Important?   

Smart gadgets, smart homes, smart agriculture, and smart cities have all been made possible by IoT. It has allowed people to live efficiently and live smartly. And it’s not just about everyday life - it’s about everyday business, too. Many sectors and industries, including manufacturing, telecommunications, energy, transportation, and healthcare, make extensive use of this technology, and companies are seeing some incredible benefits, such as:  
 
- Increasing business value
- Improving decision-making with data-driven insights  
- Automating processes and reducing labor costs
- Improving customer experience  
- Increasing operational efficiency  
 
By simply facilitating communication between objects and devices that can increase productivity, cut expenses, and produce better business results, IoT technology has the power to revolutionize industries.  
 
Software Development in IoT apps
 
So, we’ve established that the IoT has the power to transform our world, but what makes this technology so successful? The answer lies in embedded software development – the crucial component in enabling seamless integration and functionality of IoT devices.  
 
Embedded software development corresponds to the programming and application of features in gadgets like wearables, appliances, mobile phones, and sensors so that they can communicate using IoT protocols.
 
The capacity to integrate different technologies and enable them to work together effortlessly, to translate machine language from one device to another automatically, and to facilitate the easy, elegant exchange of information is why embedded software development is the key component in developing IoT applications.  
 
Here are some additional points of importance to consider.  
 
Data Management and Analytics

Effective analytics and data management are essential since IoT applications gather large volumes of sensor data, which require efficient processing and analysis. Acquiring and integrating sensor data entails gathering information from multiple sources and devices, so data filtering and real-time processing guarantee quick extraction of that pertinent information.
You need to know how to handle massive data volumes and scale databases to satisfy the expanding requirements of IoT applications. Moreover, you can extract valuable information from IoT data with the help of analytics and insights. IoT apps can extract insights and make wise decisions from the gathered data using methods like machine learning and predictive analytics.
 
Programming languages  

IoT development uses a variety of programming languages and frameworks. Due to their efficiency and close-to-hardware capabilities, C and C++ are popular for low-level and resource-constrained devices while higher-level IoT applications that demand quicker development cycles and flexibility use Python and Java. IoT systems that use web-based interfaces often use JavaScript.  
 
Testing and QA

The variety of devices, interoperability problems, and network reliability issues make testing of IoT software challenging. Examining responsiveness, scalability, and dependability of IoT-systems under different loads and circumstances requires performance and reliability testing to find and fix potential flaws in IoT applications and defend against possible cyberattacks. Therefore, security testing is essential.
 
IoT software development is set to face both exciting opportunities and formidable challenges in the future, with emerging technologies like edge computing and distributed intelligence allowing data processing and analytics to happen closer to the source of the data.
 
Development in AI and machine learning techniques will improve the capabilities of IoT applications. It will make predictive analytics, anomaly detection, and autonomous decision-making possible, making this an exciting time for all working in this field.  
 
With the IoT ecosystem expected to grow exponentially and experts predicting there will be over 50 billion, and even up to 100 billion, devices connected to the internet by the end of the decade, it’s easy to anticipate that interest in this field from average users, investors and engineers alike, will also continue to grow.  

We live in a world continuously reshaped by rapid technological transformation, touching on every aspect of our lives. More and more companies are incorporating digital services and automation capabilities, so demand for software development is higher than ever.  
 
To meet this accelerating need for digital services, software companies need to manage their projects as efficiently as possible and maximize their value. Most people are familiar with the term “Project Management” in software development – the process of planning, executing and delivering software on time and within budget.
 
Its main goal is to balance the budget, time, and human resources optimally so that the software development teams can work with little or no hassle throughout the entire software development lifecycle. It makes no difference whether you’re a leading tech corporation or just a startup – your software development projects require a certain level of expertise and management if you want to ensure successful implementation and avoid potential failure.  
 
Software project management can be categorized into 6 stages.  
 

• Initiation phase – Identifying the stakeholder’s expectations and estimating the project scope, duration, and efforts before moving on to planning.
• Planning phase – Creating a detailed development process timeline, including management of resources, risks, tasks, and staff.  
• Development phase – Overseeing the process of writing and developing the code while measuring progress and performance to check if everything runs according to plan and reporting on the project.  
• Testing phase – Staying informed on the results to ensure they meet the quality standards and stakeholder expectations.  
• Deployment phase – Taking the necessary steps to ensure the software is deployed to production and taking it live.  
• Closing phase – Documenting the entire process, gathering internal and external feedback, and evaluating the project's success.  

 
Depending on how complicated the software is, a single project can last up to several years, so an efficient and strategic approach to software project management is vital.
 
Here are three practices that will significantly impact the efficiency of your software project management.  
 
Choosing a suitable methodology
  
Choosing the most suitable project management methodology for the company and the team is essential. There are many methodologies executives can choose from based on focus and approach. For example, the traditional “waterfall” methodology is comprised of static phases that are executed in a linear order with limited flexibility, while the “agile” methodology focuses on continuous improvement throughout the development process and delivering better solutions. Also, these two can be combined into a hybrid methodology that applies the best of both worlds. This hybrid methodology can take planning following a waterfall approach, while later phases, such as development and implementation, can follow an agile approach. There is a plethora of other methodologies companies can choose from that will best suit their structure, hierarchy, employees, corporate culture, technology, etc. Executives need to choose and follow a single methodology because this will be the framework of their project management process.
 
Setting clear and realistic goals
 
Ambiguity and lack of clarity create frustration within the team and increase the chances of project failure. Therefore, goals and requirements must be clearly defined from the very beginning. Setting realistic and achievable goals is also a must. The team needs to know the work scope, the objectives of the project, and what’s expected out of every one of them. So, the goals must be clear, realistic, measurable, and achievable. Setting ambiguous and unrealistic goals that the team doesn’t understand and can’t achieve isn’t favorable for the project manager, the executives, or the company. Project goals need to be broken down into smaller goals and objectives that are realistic and achievable within reasonable timescales, which will help to ensure the project progresses as planned.  
 
Creating the right project team 
​
The project outcome depends on the project team. Often, a solid team of experienced professionals with the right set of skills and attitudes is what leads to the project’s success. Creating the right team for the job means handpicking the people whose skills and experience align with the project’s requirements. Aside from technical skills, other things to look at are attitude and communication skills, which means determining the individual’s reliability, accountability, proactivity, flexibility, and ability to give and receive feedback openly and transparently.    
  
The biggest advantage of efficient project management is that it generates efficiency in the team, directly contributing to the company’s overall success. By freeing up resources and letting people focus on the product rather than the process, efficient project management allows team members to use their time efficiently and produce their best possible work, which means the client will receive the best possible product.  

In the dynamic world of IT, the roles and responsibilities of professionals continue to evolve. Two key players in the tech industry, Platform Engineers and Software Engineers, often find themselves at the forefront of innovation. But what exactly sets them apart? Let's dive into the realm of Platform Engineers vs. Software Engineers to shed some light on these distinct roles.
Platform Engineer: Building the Foundation 
Imagine you're constructing a skyscraper. The Platform Engineer is the architect who designs the sturdy foundation and the structural framework that supports the entire building. They focus on creating the environment and tools necessary for software applications to run seamlessly.
 
Here's a closer look at their key responsibilities:
 

• Infrastructure Management: Platform Engineers deal with servers, networking, and cloud infrastructure. They ensure that everything runs smoothly, from provisioning servers to managing databases.

 

• Automation: Automation is their best friend. Platform Engineers use tools like Docker and Kubernetes to automate deployment and scaling processes, reducing manual effort.

 

• Security: They're responsible for fortifying the infrastructure against cyber threats. Security protocols and best practices are integral to their role.

 

• Monitoring and Optimization: Platform Engineers keep a watchful eye on system performance, identifying bottlenecks and optimizing resources for efficiency.

 
Software Engineer: Crafting the Code 
Now, think of the Software Engineer as the interior designer of our skyscraper. They're responsible for the aesthetics and functionality of each room within. Software Engineers write the code that brings applications to life.
 
Here's a glimpse into their world:
 

• Coding: Writing clean, efficient, and bug-free code is their forte. They're proficient in various programming languages, depending on the project requirements.

 

• Testing: Software Engineers rigorously test their code to identify and fix issues. They ensure that the software works as intended and meets user expectations.

 

• Collaboration: Collaboration is key. They work closely with designers, product managers, and other team members to translate ideas into functioning software.

 

• Continuous Learning: Technology evolves rapidly, and Software Engineers must stay up-to-date with the latest tools and frameworks to remain effective.

 
The Overlapping Skills 
While Platform Engineers and Software Engineers have distinct roles, there is some overlap in their skill sets. Both need strong problem-solving skills, attention to detail, and a commitment to quality. Effective communication and teamwork are also crucial for success in either role.
 
In conclusion, Platform Engineers and Software Engineers play complementary roles in the IT industry. Platform Engineers lay the foundation for software development, ensuring a stable environment, while Software Engineers bring applications to life with their coding expertise.
 
Both are indispensable in the tech world, working hand in hand to create the innovative solutions we rely on every day. So, whether you're drawn to building the infrastructure or writing the code, there's a place for you in the ever-evolving landscape of IT.
​

Imagine you had to draw a picture of a house without ever having seen one. Imagine someone telling you to define a word you have never heard of. This is what working on a software project without proper code documentation looks like. Code documentation is the sore spot of every software development company.

Ok, but what is software code documentation?

Code documentation is one of the core parts of a software project. Basically, it is the guide to the code – it shows what the code is, what it does, and how it does it. It also helps other developers in case they need to modify or fix the code in the future.

Now, we will dive a little deeper into the topic.

Why do we need code documentation?

Let’s look back and try and remember how many junior developers we have seen in utter confusion and panic because they've been assigned to a project where they did not understand the code. And this is not just junior developers' problem. Even seniors and highly experienced industry professionals have trouble joining a project, modifying, or fixing a code without documentation. Proper documentation offers easier onboarding of new team members, easier collaboration when multiple developers work on the same project, easier maintenance, and all-around better long-term management.

What types of code documentation are there?

There are two types of documentation – internal and external.

Internal code documentation is done directly in the code as short comments that explain the code or the algorithm. This is also known as inline documentation, which is usually concise, simple, and aimed at other developers.

External code documentation exists outside the code, and it's more comprehensive than inline comments. External code documentation gives a complete system description, including its architecture,
interfaces, and functionality. Besides informing other developers, external documentation is often used for a wider audience, like project managers and clients.

What are the long-term positive effects of code documentation within the company?

As previously mentioned, prioritizing code documentation within the company is extremely important. By having all the puzzle pieces and a clear image of the project scope, people work more efficiently and effectively, thus minimizing the potential for mistakes. Setting standard documentation procedures and
processes helps collaborators catch up quickly, keep track of changes and work more autonomously.This, in turn, increases independence and promotes self-confidence among employees. It also helps managers rest assured, knowing that the flow of projects will not be interrupted when onboarding new people. There are also significant financial benefits when we consider the fact that code documentation prevents unnecessary waste of resources – rather than spending a portion of their workday searching for information, developers can be productive and efficient with their time.

Ultimately, when we look at the big picture, it might even be safe to presume that code documentation is almost as important as the code itself, as prioritizing comprehensive documentation brings companies a step closer to ensuring a seamless workflow.

Open your web browser today, and you’ll find at least one piece of news related to artificial intelligence. Whether you work in IT, healthcare, legal, marketing, or any other industry, AI is the most widely discussed topic, and rightly so – its potential is endless. 

Regardless of the industry you are working in, you have almost certainly encountered one AI tool or another (and if you haven’t you are bound to sometime soon), but the question is, are you using it right?  

Are you fully taking advantage of the potential of AI? 
Unfortunately, many people fall into one of 2 categories: they either perceive AI as a sci-fi product that will take over the world and refuse to go anywhere near it, or they use it incorrectly and end up disappointed by its performance simply because they treat it like something that it’s not – they treat it like Google.

So, rather than typing in simple and basic questions, as you would in a search engine, try communicating with it as you would with a person – the more knowledge and information you feed it, the better response you’ll get. Unlike traditional search engines, AI doesn’t fall short when you get specific. On the contrary, that’s when you see its full power.

Here are 5 ways to use AI for performing practical tasks:  

1. Write code.  
You can use AI to write code, regardless of whether you already know how, or not. GPT-3.5 is great for those who already know how to write code, while GPT-4 is an amazing tool for those who have no previous experience. Just by typing in a description of what you want, these tools will give you a step-by-step guide of what you need to do and will literally write the code you need. This doesn't mean it can replace programmers and developers, but it does give them a head start and makes things significantly easier. (Read our article for secure coding before you ask AI for solutions) 

2. Create a marketing strategy.  
First, give the AI tool information on your product or service, or even better, ask it to gather information through deep analysis. Then, give it a role from which to approach the creation of the strategy. For example, tell it to act as a marketing manager. And finally, ask for specific things - like a social media strategy. Give specifics on the product, the role, and the outcome. It can help save time for advertising agencies or marketing managers.  

3. Write.
Chat-GPT can write entire essays on your behalf. But, if you give it a basic topic, it will spit out equally basic and boring answers. So, instead of typing “Write an essay on global warming” type in “Write an essay on the following points: Global warming, Negative side effects of global warming, How to prevent global warming” etc. 

4. Create images.  
Midjourney is an AI tool that is simply amazing when it comes to generating images. By typing in highly detailed prompts where you describe what you want to see, you create entirely new images. AI is also now integrated into Photoshop, so instead of manually changing things, you can type in specific, detailed prompts about the changes you want to make. It will make a significant difference for graphic designers, fashion designers, animators, filmmakers, and anyone in the visual arts industry.  

5. Brainstorming. 
When it comes to generating ideas, AI is the perfect tool. Good ideas are a numbers game – the more you have, the higher the chance to stumble across a great one. Again, you have to be specific, to tell it how many ideas you want and what they should revolve around. For example, type in “Give me 10 ideas for an amazing sports website”. You can ask it to come up with anything – an idea for a new business, a service, an application, and so much more. As we said, not all ideas will be great and groundbreaking, but the more ideas you ask it to generate, the greater the chance for it to come up with a good one – or at least give you inspiration for something you can then add to and work on. Every industry revolves around generating new ideas, so being able to use AI in this capacity is to everyone’s advantage.  

When used properly, AI can multiply and accelerate human effort – it’s not here to replace us. And the best thing about it is that it can take over those tedious tasks that often exhaust us, freeing up our energy and potential to do the things we love with the unique human touch.