Feb 29, 2024

12 min read

No Data, No AI – The Game Changing Role of Self-Powered Sensors

We have well and truly entered the era of AI - whether it’s through self-driving cars, language processing chatbots or state-of-the-art diagnostic tools, AI is well and truly changing the texture and feel of the world around us. AI’s dramatic rise is only set to continue in the coming years - PwC predicts that AI will contribute a staggering $15.7 trillion to the global economy by the year 2030! But AI needs data to function - the quality of an AI’s predictions and decision-making is only as good as its data set. In this article, we explore how self-powered sensors allow AI systems to dig their tendrils into the physical world, making them an indispensable part of our future’s AI solutions.

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We are living in the age of artificial intelligence. AI’s star is truly on the ascendancy. Artificial Intelligence is now so thoroughly permeated into our everyday lives that we don’t even notice it most of the time. From driverless cars zooming through our streets, to virtual assistants curating bespoke shopping experiences, artificial intelligence has really penetrated deep into the structures that underlie our everyday lives. 

The possibilities that AI opens up are immense - truth be told, nobody knows how far we can take this technology - it’s still very much in its adolescence. Computational intelligence was once something limited to the pages of science fiction but today, we are standing at the precipice of a whole new paradigm.

AI’s transformative power has already started changing the way we interact with technology - ChatGPT is a great example of how AI is starting to feel indispensable to the everyday tech-user - much like Google, a couple of decades ago. 

So, what makes AI so powerful?

At the core of AI’s power is its ability to analyse unimaginably huge datasets, recognise patterns, learn from them and subsequently make decisions with little to no intervention. This is the underlying principle that allows AI to disrupt such a diverse range of fields - be it healthcare, where AI-driven algorithms make high-quality diagnoses that put seasoned physicians to shame; or finance - where AI-based models identify market trends ahead of time and inform prudent investment strategies; or nature protection, where AI-powered systems monitor large ecosystems in real-time, enabling proactive responses to impending threats, both manmade and natural. 

Artificial Intelligence is able to go through tons more data, more quickly than any human or set of humans could ever hope to. This is what makes it so efficient and powerful. 

It would be fair to say that a big part of AI’s might is due to our data collection capabilities. AI is nothing without large amounts of data. 

Name of The Game Is Data Collection

AI is only as good as the data that it has at its disposal - all AI systems are essentially pattern-recognition and matching systems that work with a high degree of sophistication. They learn to match patterns by being trained on massive amounts of data - which they use to identify correlations and create decision-making heuristics. 

The quality of the data has a direct impact on the efficacy of the AI system. This is important to understand because there is a common trap that people and companies fall into when they think of AI as some kind of a magic bullet - a mythical solution that can plug holes in any system or fix any problem. That’s hardly the case. 

AI is better understood as a fast and efficient way of organising and retrieving large amounts of information. Granted, that’s a bit of an oversimplification, at least with respect to some of the more advanced AI systems going around today. But, it’s not too far off the mark. 

The idea we’re getting at here is this - organisations often place too much focus on the AI model itself, and not enough on the data it works with. Collecting, cleaning, labelling and maintaining a high quality data set is hugely important - probably more so than how fancy the AI algorithm is. A hugely capable AI engine that runs on poor data is just no good. The converse - a reasonably simple AI system that works on a huge amount of high quality, well organised data can be a hugely powerful tool. 

AI systems that are based on biased or inaccurate data will inevitably inherit those biases and inaccuracies. This can lead to disastrous outcomes and skewed decision making - imagine that happening in a healthcare setting for instance - it could mean the difference between life and death. 

AI systems gather data in a number of ways - direct data collection methods like web scraping, sensors, surveys, user interactions etc; they could leverage pre-existing data sets or simulate artificial data sets. However, all of these data harvesting methods are digital-only except for sensors. 

Wireless sensors are the only way for AI systems to gather data from the physical world, as it were. Wireless sensors act as eyes and ears for AI systems, on the ground, feeding them data in real-time.

Wireless sensors allow AI systems access to a practically endless feed of raw data - enabling them to make decisions that are highly accurate and relevant to the ground realities pervading a given situation. Today, thanks to the advent of energy harvesting technologies, we are seeing the emergence of self-powered, battery-free sensors that can be deployed pretty much anywhere, irrespective of location or accessibility. Add to this the vast internet coverage made possible by 5G and we have a recipe for some majorly disruptive transformation. 

This is especially the case in remote use-cases where self-powered IoT sensors make sure AI systems are supplied with a relentless stream of accurate, real-time data. In use-cases such as precision agriculture, this is invaluable to the accuracy and precision of an AI system’s decisions.

The Symbiosis Between IoT Sensors and AI

The meteoric rise of AI over the last few years has coincided with IoT’s similar trajectory. Both these technologies stand as the cutting edge of information technology, dramatically transforming nearly every aspect of human life today. 

IoT, in essence, refers to a system of interconnected nodes that are able to communicate with one another independently - these nodes today have become so small and powerful that we are able to deploy hundreds if not thousands of them in locations as remote as coal mines and forests

IoT systems, through their wireless sensors, are able to collect a continuous stream of data from their surrounding environments - this can be any kind of data - temperature, heat, moisture levels, light, sound - well you name it! This makes them a perfect companion for the analytical prowess that AI systems bring to the table. 

The data that IoT sensors collect is raw - when this raw data is fed into AI systems, it allows them to create predictions and insights or even intervene in meaningful ways. For instance, the heart rate data from a fitness tracker, temperature data from a farm or traffic flow data from a smart city, when funnelled into AI systems, could act as precious fodder that helps us glean a hugely diverse range of actionable insights. This allows AI to extend its reach into the physical world, making it a much more powerful and versatile tool in our technological arsenal. 

This is a symbiotic relationship at its best - without the analytical might of artificial intelligence, the huge amounts of data that wireless sensors gather is next to useless. Similarly, without rich troves of high quality data, the most sophisticated AI system has nothing to work with - they need each other and enable each other in the most fundamental of ways. 

Imagine self-powered sensors powered by energy harvesting embedded in buildings, bridges, factories, farms or traffic lights, silently gathering endless streams of data, without any manpower or battery replacements. This could pave the way for a truly smart ecosystem where data flows seamlessly across platforms, applications and modalities, making life easier in the process. 

Data from wireless sensors can be used by AI in multiple ways - real-time monitoring where wireless sensors keep a live relay of data running continuously, enabling the AI system to analyse the incoming streams in real-time, make decisions on the go and adapt while running. This could be best imagined as part of an AI-based patient monitoring system or traffic-flow monitoring system, where delays simply can’t be afforded. 

Then, we have a predictive analytics kind of use-case, where AI models trained on historical data can make data-driven predictions pertaining to impending events - for example, think of a system designed to predict and prevent equipment failures; or an AI-powered weather forecasting system. 

Thirdly, we have pattern recognition. This is where AI identifies covert patterns in highly complex sensor data, unearthing insights that would have otherwise been nearly impossible to spot. Think early disease detection, consumer behaviour analysis etc. 

Lastly, sensors can be implemented in automation and control systems that use the data input to actuate interventions autonomously, without any human interference e.g. driverless cars, smart home technologies, robotics etc. 

The possibilities are endless for innovation and disruption when AI and IoT sensors join hands. 

Use Cases for Batteryless Sensor-based AI

Let’s take a look at some examples of how battery-free sensors could be used along with AI in real-life scenarios. This is by no means an exhaustive list - just a few relatable use-cases. 

1. Autonomous Vehicles

Self-driving cars and other forms of autonomous, unmanned transport such as drones require a continuous stream of data - this is made possible by wireless sensors (LIDAR, cameras, radar etc). This continuous data stream is crucial for them to navigate environments safely in real-time, avoiding obstacles and potential threats. 

These vehicles often come with integrated sensors that are able to harness and process large amounts of data on the go, constantly keeping the vehicle’s AI system updated on its surroundings. 

2. Healthcare

This is by far the most exciting use case for batteryless sensors and AI. Energy harvesting sensors enable continuous monitoring devices that can track various biological and biochemical parameters in a patient, remotely. 

For example, imagine a heart rate sensor that tracks a patient’s heart rate data continuously and relaying it to the back end where an AI system monitors the data and slices it to identify patterns. When the AI detects an aberration, it alerts medical personnel immediately, potentially saving the patient’s life. 

This is just one example of what could be done using IoT sensors and AI in the field of healthcare. The possibilities are endless. Personalised healthcare could get a big boost with this kind of a setup. 

Sensors and AI can also enable people to enjoy more sovereignty over their health and well being by making a huge array of data-driven metrics available to them. This could enable a more holistic approach to healthcare where the individual has enough information at their disposal to make better health choices over a period of time. 

3. Smart Agriculture

This is an application that’s growing in popularity at a tremendous rate. Today, smart farms deploy hundreds of batteryless sensors that monitor various parameters such as temperature, soil pH, moisture, mineral level etc. 

These wireless sensors provide AI systems with data which they use to optimise irrigation, planting, pest control, fertiliser use etc. Access to rich data streams enables farmers to make sure their yields stay high in spite of threats like erratic weather patterns and pests. 

4. Industrial IoT (IIoT)

Self-powered IoT sensors are being used along with AI in industrial settings to monitor the conditions of heavy equipment and machinery. They also help keep track of operational efficiency and impending maintenance needs - i.e predictive maintenance. 

5. Smart Buildings

Batteryless sensors are deployed in smart buildings for a variety of purposes - they collect data on various parameters such as energy usage, occupancy and environmental conditions within a building. 

AI uses this data to economise energy expenditure and offer more comfort and convenience to the occupants of the building. This kind of a setup is what we’re going to see in a lot of homes in the coming years with smart home technologies becoming increasingly popular. 

Batteryless Sensors Right For AI’s Future

Energy harvesting powered sensors are practically a necessity for the future of AI. As AI continues its trend of explosive growth and expansion, we are seeing a dramatic increase in demand for remote sensing capabilities that battery-powered sensors and other data-collection modalities simply aren’t able to meet. 

Batteryless sensors have a few aces up their sleeve in this regard. First off, there is the sustainability aspect - self-powered sensors harvest energy from their environment. So, they don’t need any batteries. This makes a huge difference, at scale, to the problems of mining for rare minerals and toxic battery waste. The absence of a battery also means that these energy harvesting powered sensors require less maintenance and cost less to run than their battery powered counterparts. They also last longer. 

Moreover, batteryless sensors totally eliminate some big hazards associated with batteries such as leaks and explosions - this is a very important point to consider when we take into account the fact that most of these sensors are going to be deployed in far flung areas, far from human supervision - or at least that’s the idea. 

The absence of a battery makes these self-powered sensors very compact and diminutive, making it easy for them to be embedded into various kinds of systems. 

Last but perhaps most importantly in the context of AI systems, battery-free sensors are able to offer continuous operation - this is a huge plus point in difficult environments. They are able to harvest as much energy as they need, store it in capacitors and keep up with the demands of the system without ever running out of juice. 

Garbage in, garbage out

Garbage in, garbage out goes the adage - it sums up the relationship between AI and data perfectly. Without high-quality data sourced from a diverse range of sources - data that’s representative of various kinds of permutations and combinations - AI systems are effectively crippled. 

This is why self-powered sensors represent a huge leap forward for the future of AI. They enable reliable, long-term data collection that’s continuous, seamless, cost-effective, reliable and perhaps most importantly, environmentally sustainable. 

The integration of self-powered sensors and AI is not just a matter of iterative development - it’s much more radical than that - it’s a proper paradigm shift. Powered by batteryless sensors, AI can truly spread its wings and go places that were unimaginable even a few years ago. Thanks to reliable batteryless sensors, today, we are able to harness the might of AI in very remote use-cases where access to power can be a huge problem. 

The future of AI looks bright - it looks all set to deliver on its huge promise of reshaping the world, thanks to the silent, continuous humming of batteryless sensors in the background!

About the author

Abishek Swaminathen

Senior Content Manager

Abishek is ONiO’s senior content manager. A medical doctor by profession, he stumbled onto a writing career almost by accident, as it were. Words have enthralled Abishek since the day he first held a book and at ONiO, he channels his inner wordsmith towards providing our subscribers with regular doses of fun and informative content.

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