The Legit Baines Blog

I'm Trying to Get Better at Everything (and Accidentally Building another IoT Network at the same time) I don’t really know where I’m going in tech yet — and for a while, that bothered me. There are so many different paths: backend engineering, embedded systems , web development, networking… and it feels like everyone else has already picked a lane.  I’m trying to see that as a strength rather than a weakness. Instead of specialising too early, I’ve been focusing on getting better at as many areas as I can. Not in a scattered way, but by building things, testing them and testing myself as I go. One of the best examples of that mindset has been my recent dive into IoT . How I've Ended Up Building another IoT System Someone told me about their business idea and it involves IOT which was a big part of my course at Hallam University so I told him that I'm probably the ideal person to build him a prototype IoT system that he can present to his potential funders.  He knows more ...

Hallam University Taught Me New Things Plus Also How to Learn Even More Now that I've finished my university journey, I’ve been reflecting on how much I’ve grown, not just in terms of knowledge, but in the very process of learning itself. University has opened my eyes to entire worlds of technology I never imagined exploring, from databases to Artificial Intelligence (AI), and from the Internet of Things (IoT) to programming. But what stands out most to me is how university has taught me not just new things, but also how to learn new things, even on my own. The New Things I’ve Learned When I first walked into university, I had a basic understanding of technology and programming. But the subjects I’ve encountered throughout my studies have completely transformed my perspective on what is possible. Here are just a few of the most exciting things I’ve learned: 1. Databases Learning about databases has shown me how the power of data is structured, stored, and retrieved. I never tr...

I have always been good with numbers, when I was at school I did my Maths GCSE a year early and got a B. Unfortunately I had a lot of bad things going on in my life at the time so I didn’t go forward with University at that time.  Fast forward a decade or two and now I’m a recent graduate from Hallam University , I went there as a mature student to do a degree in computing and the course involved loads of data related modules. During my Computing course at Hallam University I spent a lot of time learning about data, databases, data cleaning , data processing, data management, data analytics and data visualisations . The course also involved a number of assignments that included a power point presentations in front of tutors and answering their questions about the work afterwards. Presentations were something I was very comfortable doing. I learned to collect raw sensor data using a Raspberry Pin (or from a pico using micropython/circuitpython), I learned that it is absolu...

 Becoming an IT Graduate as a Mature Student: The Reality No One Talks About Going to university as a mature student was one of the hardest and most rewarding things I’ve ever done. Studying IT later in life meant juggling responsibilities, self-doubt, and the pressure of starting again in a completely new industry. Graduating felt like a huge achievement. But stepping into the job market as a new IT graduate who isn’t new to work at all came with its own set of challenges. What I quickly realised is that breaking into IT as a mature graduate isn’t just about technical skills. It’s about confidence, reframing experience, and learning how to tell your story in a way employers understand. Sheffield Hallam University Challenging the Assumptions of Employers and Recruiters One of the first hurdles I encountered was assumption. There’s a quiet expectation in some recruitment processes that a “graduate” is young, fresh out of university, and at the very start of their working life. ...

What My RiverProject is about and Why Sensor Data + MQTT is Revolutionising Environmental Monitoring  💻📶📡📠📉📊📈💹 River Project Repository My  RiverProject , hosted on GitHub, is an ambitious and practical environmental sensing system I built as part of my Year 2 project at Sheffield Hallam University. The core of the project involves collecting real-world sensor data - from a Sense HAT attached to a Raspberry Pi processing that data, and sending it in JSON format via the lightweight messaging protocol MQTT so it can be visualised and analysed elsewhere. GitHub At its heart, RiverProject exemplifies a modern approach to environmental monitoring: shifting away from manual data collection and towards continuous, automated remote sensing . In my project I gather environmental data, create rolling averages, and publish that information through MQTT to other platforms for dashboard visualisation - which can be invaluable for spotting trends or triggering alerts. GitHub Why...

  5 Reasons Why AI Tools Can Be Useful — And 5 Reasons Why AI Is Becoming a Bubble Artificial intelligence has quickly become the center of global attention. It promises efficiency, creativity, automation, and entirely new business models. But as the hype grows louder, so do concerns that we may be entering bubble territory — a cycle of inflated expectations, overinvestment, and unrealistic assumptions about what AI can deliver. Below is a balanced look at both sides: why AI tools truly are useful, and why the current boom may be a bubble in the making. 5 Reasons Why AI Tools Can Be Useful 1. They dramatically speed up repetitive work From drafting documents to generating code templates, AI automates time-consuming tasks. This frees humans to focus on higher-level judgment, strategy, or creativity. 2. They democratize access to advanced capabilities You no longer need to be a programmer, designer, or data scientist to perform tasks once reserved for specialists. AI expands...

 💻💻💻 Staying health- and safety-aware can be surprisingly difficult when your job keeps you glued to a screen, focused on reports, dashboards, and deadlines. These simple but effective tips will help you protect your wellbeing while maintaining productivity. 1. Prioritize Proper Desk Ergonomics 💺💺💺 Set up your chair, monitor, and keyboard so your body stays in a neutral, supported position—this reduces strain on your neck, shoulders, and back. 2. Follow the 20-20-20 Rule for Eye Health Every 20 minutes, look at something 20 feet away for 20 seconds to reduce eye strain from extended screen time. 3. Take Scheduled Micro-Breaks Short, regular breaks improve your comfort and concentration—set reminders to stand, stretch, or walk for a minute or two. 4. Keep Your Workspace Clutter-Free A tidy area prevents trip hazards, spilled drinks on electronics, and the stress that comes from a chaotic environment. 5. Stay Hydrated Throughout the Day Drinking enough water keeps yo...

  Let’s be honest — when people hear “data analysis” , they often picture spreadsheets, endless rows of numbers, and someone yawning behind a laptop at 2 a.m. But that’s a myth. Data analysis isn’t dull — it’s detective work, creativity, and storytelling rolled into one. If you’ve ever dismissed it as boring, it’s time to think again. Here are 7 reasons why data analysis is anything but boring: 1. You Get to Solve Real-World Mysteries Data analysts are like modern-day detectives. Every dataset hides clues that reveal why something happened or how it could change. Whether it’s uncovering why sales dipped last quarter or predicting the next big trend, you’re constantly piecing together a puzzle — and few things are more satisfying than cracking the case. 2. It’s a Gateway to Understanding Human Behavior Data tells stories about people — what they buy, how they think, where they spend their time. Analysing data gives you a front-row seat to human patterns and decision-making...

Beginners guide for using the Machine Learning and/or AI tools on google.colab for a complete beginner:  AI and ML is all about analysing data so first you need to decide what kind of data you want to analyse. ( I refer you back to my previous blog post beginners guide to AI and ML terms. .) Basically do you want to analyse numerical data , text or images ? On this occasion I’m going to keep it simple and create some data visualisations  (graphs) You can get free open source data from this website kaggle.com I downloaded this file in .csv format: s-p-500-time-series-forecasting-with-prophet/input   Next find this website colab.research.google.com https://colab.research.google.com This is when you can go to chatgpt and ask it to write the code for google colab to analyse the data in  the way you want for example you could ask it to write the code to create a dataframe from that data:    Drag and drop the csv file into google.colab Change the labels s...