Water utility operators around the world are under continuous pressure to operate efficiently, conserve water, reduce their environmental impact, and maintain a high level of supply and availability. The adoption of IoT sensors and artificial intelligence (AI) can help the water industry become more resilient and efficient. Many water utilities have started to implement technology such as IoT-connected sensors on pumps, valves, and meters, along with geographic information systems (GIS), supervisory control and data acquisition (SCADA), and advanced metering infrastructure (AMI). Each of these technologies helps to improve operations, and combined they produce a large volume of real-time data to which operators can apply artificial intelligence predictive modeling. Let's take a look at five benefits of IoT and AI.

The mix of IoT and AI is being used by tech enthused agencies for curbing the rise of coronavirus cases, and flattening the curve. By the time you finish reading this article, the number of new coronavirus cases would have increased in tens of thousands. While the world has slowly started to live and adapt in this environment as a new norm, scientists and tech enthusiasts around the globe have not settled down. They are constantly finding new ways to curb the COVID-19 rise. One of the ways they have been working is the adoption of technologies – to be more precise, AI and IoT technology. Let's look into how these two technologies are bringing the world closer to a time where we will have a better control of the situation.

When we talk about environmental sustainability, we often refer to the negative impact of technologies on the world around us. Yet if we dwell more on the use than the potential of specific innovations, we see that it all depends on how we choose to act. In fact, among the innovations of the Internet of Things and Artificial Intelligence, several can help companies increase the levels of environmental sustainability of their processes if used correctly. Here's how Artificial Intelligence and IoT can improve environmental sustainability. "development that meets the needs of the present without compromising the ability of future generations to meet their own needs."

The Indian logistics industry has traditionally been a fragmented one with a lot of inefficiencies. The cost of logistics in India today amounts to approximately 15 per cent of the nation's GDP, as compared with developed countries where it's around 7-8 per cent of their respective GDPs. This is certainly a significant drain on the economy and negatively impacts sectors such as agriculture and manufacturing, as most Indian companies have had limited visibility into their respective supply chains. However, since 2015, we have noticed a paradigm shift in the government's policies and approach towards this sector, which is enabling seamless integration of operations to make it more organized. Beyond the policy push, today new-age technology is playing a huge role in redefining and revolutionizing various industries in our country, and the logistics industry is no exception.

Due to mobility restrictions and limited supplies of essentials, the pandemic highlighted the importance of commercial vehicle fleets. It also emphasized the importance of technological solutions for effectively managing commodities movement. According to Fortune Business Insights, the global fleet management software industry will develop at a compound annual growth rate (CAGR) of 18.3 percent between 2022 and 2029. Fleet-tech is about utilising the capabilities of the Internet of Things (IoT) and Artificial Intelligence (AI) to achieve efficiency (AI). The drivers, their "khalaasis" (navigators), fleet managers, and fleet owners are at the heart of commercial fleets.

One regular Tuesday morning I was looking for new papers on edge Internet of Things networks, like we all do, and came across a new term called Federated Learning and immediately went on a quest to understand this technique. Federated Learning(FL) in its simplest form is a union between the vivacious worlds of Machine Learning and the Internet of Things. It is an ML-based solution that improves the functionality of edge devices in IoT networks. Edge devices in an Internet of Things network are the mobile devices that collect data and help in achieving the purpose of the network remotely instead of the traditionally connected nodes in a network. Our smartphones are the most common example of edge devices. According to the Google AI Blog from 2017- "Federated Learning enables mobile phones to collaboratively learn a shared prediction model while keeping all the training data on the device, decoupling the ability to do machine learning from the need to store the data in the cloud."

The last thing you probably need to read is yet another article describing the value of edge computing. Let's face it: 99% of the content out there now on this topic is not meant for you. But it says something (scary) when a recent article from tech industry booster Wired Magazine contains the statement "Big Tech–currently best known for breaking democracy, enabling the spread of medical misinformation, and knowingly endangering the mental health of children…." Artificial intelligence is already well-covered in dystopian views of the future. To some degree, IoT has gotten off a bit easier because it feels tactical and industrial – all these little bits of data being generated by sensors and machines.

"This does not include a broad range of'hidden' costs, including reduced vehicle value (typically anywhere from $500 to $2,000), higher insurance premium, legal fees, driver turnover (the average driver replacement cost $8,200), lost employee time, lost vehicle-use time, administrative burden, reduced employee morale and bad publicity," said Yoav Banin, chief product officer at Nauto, which provides artificial intelligence driver and fleet performance solutions. Emphasis on truck driving safety is well placed, considering other challenges that the trucking industry is facing. Ranking first is a chronic shortage of truck drivers nationwide that could force fleet operators to hire less-experienced drivers who require operator and safety training. Driver compensation and truck parking ranked second and third, but immediately behind them in fourth and fifth position were driver truck fleet safety and insurance availability, which depends on safe driving records. Historically, fleet operators managed safety risks with training programs, manual coaching sessions and manager ride-alongs with drivers.

Enterprises around the world are widely adopting artificial intelligence. The Internet of Things (IoT) is not far behind either. In fact, with IoT making it easy to collect and share data across a network of devices, it has become a must-have for many industries. However, you need advanced tools and technology to process and analyze the data collected by IoT. That's why large enterprises have been investing in artificial intelligence to streamline and automate business processes.

In today's tech-savvy world, it is really fascinating to see millions of devices talking, exchanging data and transforming valuable insights into vital courses of action. Thanks to the Internet-of-Things (IoT) and Artificial intelligence (AI) which has transformed the business world by storm. Indeed, they have made businesses less dependent on humans and more dependent on machines. The result is ultimately auspicious! Now, it is easier for companies to aggregate a tremendous amount of data, analyze and make fearless decisions to take a big leap in business using smart technologies.