A few months ago, I noticed that my Samsung Galaxy battery drained much earlier than it used to. After reviewing the consumption in the settings, I realized that the location service was constantly on, even when no app required it. I decided to force deactivate it in the background and the result was surprising: I gained several hours of autonomy. This small tweak led me to reflect on how unnecessary processes—both on a phone and in a business—consume valuable resources without us even realizing it.
GPS, Wi-Fi and Bluetooth location are functions that modern smartphones keep active by default to offer services such as Google Maps, virtual assistants or weather applications. However, what many users ignore is that the operating system performs periodic scans even when no app requests them. On Galaxy, the 'Improve Accuracy' option enables constant scanning of Wi-Fi and Bluetooth networks, which quietly drains the battery. By unchecking those boxes — within 'Location' and then 'Scan' — I was able to stop the device from checking the surroundings every few seconds. The savings were so remarkable that I began to wonder if there was an equivalent principle in the business world.
In the corporate arena, many organizations run applications that perform repetitive queries to databases, sensors, or external services without a real need. Those ghost processes generate infrastructure costs, increase the risk of errors, and consume bandwidth, just like GPS on a phone. The solution is not to remove functionality, but to optimize it. This is where custom app development becomes a key tool. Instead of using generic solutions that scan without judgment, companies can custom design software that runs checks only when they are needed, based on business rules or predictive models. For example, a logistics platform can avoid querying the location of each vehicle every minute, and do so only when a relevant event is detected, improving the efficiency and lifespan of the devices.
This philosophy of eliminating 'constant scanning' also applies to artificial intelligence. AI agents, when well trained, can predict usage patterns and decide when it is appropriate to activate a service. At Q2BSTUDIO, we develop AI solutions for companies that integrate machine learning models to anticipate needs, reducing unnecessary resource consumption. For example, a sensor monitoring system can learn peak times and adjust sampling rate, saving energy and costs across AWS and Azure cloud services. In addition, cybersecurity benefits from this approach: instead of scanning all ports constantly, intelligent pentesting systems are activated in the event of anomalies, minimizing exposure.
The case of my Galaxy taught me that a small but strategic change can have a huge impact. In the business environment, that 'small change' is usually the implementation of business intelligence service tools such as Power BI, which allow you to visualize exactly where resources are being wasted. With customized dashboards, managers can identify inefficient processes and make informed decisions to optimize the use of technology infrastructure. In fact, at Q2BSTUDIO we help our clients design dashboards that reveal those 'ghost scans' in their systems, proposing tailor-made improvements.
However, the analogy goes further. When I forced my Galaxy not to check location, I also had to adjust app permissions and turn off automatic syncs. In an enterprise, this is equivalent to reviewing data access permissions, backup schedules, and API integrations. A custom software solution can centralize those configurations and automate their management, ensuring that only essential processes consume resources. In addition, the incorporation of AI agents allows the system to learn from usage patterns and dynamically adjust the frequency of scheduled tasks, something impossible with standard platforms.
Personal experience with the battery led me to recommend my colleagues to check their own phones, but also to think about how companies can apply this logic. One recent customer, a retail store chain, had an inventory system that updated the location of each product every 15 minutes, 24 hours a day. By redesigning the application with event-based logic—similar to turning off constant scanning—they reduced data traffic by 70% and extended the life of their mobile devices. We developed this project in Q2BSTUDIO, combining AWS and Azure cloud services with an optimized backend and dashboards in Power BI to monitor performance. This type of custom application development proves that efficiency is not at odds with functionality, but is the result of careful design.
From a technical perspective, the challenge is similar to the one facing smartphone manufacturers: how to offer location services without sacrificing battery. The answer, in both hardware and software, is contextual intelligence. In the corporate sphere, artificial intelligence for companies allows systems to distinguish between a critical and a routine query, prioritizing the former. For example, a virtual assistant that calls a location API only when it detects that the user is moving, rather than every minute. That's exactly what we achieve with the AI agents we develop, integrated into process automation and cybersecurity solutions.
In short, what started as a gimmick for my Galaxy turned into a powerful metaphor about resource optimization. Each unnecessary scan cycle consumes power, whether it's a phone battery or a cloud server compute. Companies that adopt this mindset – questioning every repetitive process – are the ones that reduce costs and improve their sustainability. And at Q2BSTUDIO, we're committed to helping them shape that future, combining the best of custom software development, artificial intelligence, and cloud services. The next time your phone asks you to turn on location, remember that every setting decision has an impact; In business, the right consulting can make the same difference.
