IoT-AI Systems: the Near Future of Wastewater and Water Management

We have often heard people, companies or organizations giving catchy phrases and taglines about their claims on their technologies or visions representing future, for eg. the state of Florida in US openly says " The future is here" and I am not contradicting to any of them but lest we forget that evolution is the tendency of nature and we humans and our technology is a part of it so whatever technological boom we are passing through and future inventions we are looking for should be termed as the "things of near future, and two such wonderful technological marvels I refer to the things of near future are IoT viz. Internet of things and AI viz. Artificial intelligence.

Readers must be wondering why lay this emphasis on the term near future?

With all these inventions and technologies we see the future too bright and advanced, but when we look at the other side of the coin we find it a bit gleam too. Why? Because the biggest challenge of near future is water conservation, preservation and availability where even after all the efforts we are doing they still prove to be miniscule. Even this vast availability of manpower is not of much help.

So, why can't the combination of these two sides of near future can further be enhanced and evolved and make the far future brighter.

When IoT and AI are applicable in almost all the sectors, its impact is and will make things very smooth for us in terms of water management also.

. IoT and AI: THE DEFINITION

IoT is a network of machine to machine or device to device connection, which includes interconnected machines sensors and devices, operated without human interference through internet. Basically the convergence of multiple technologies, real-time analytics, machine learning, commodity sensors, and embedded systems.

In simple language, machines or commodities are connected to internet rather than people.

Although the term was first coined in 1999 by Kevin Ashton of Proctor and Gamble, the first application as such was introduced in 1982 itself in a modified Coca-Cola vending machine at Carnegie Mellon University to monitor whether the drink served is cold or hot.

Now we all are quite familiar with the term AI i.e. artificial intelligence, howsoever, another AI which is ambient intelligence is linked to IoT which is also explained further.

Artificial intelligence is basically machines or devices performing as humans or with human intelligence and IQ, from voice recognition to driving cars, from machine operation to rescue operation all can be done by machines in form of artificial intelligence, which we ourselves experience every day in the form of "SIRI or Ok Google".

While ambient intelligence and autonomous control were initially not part of the original concept of the Internet of things, it was later reinforced. Ambient intelligence and autonomous control do not necessarily require Internet structures(1).

IoT intelligence can be offered at three levels: IoT devices, Edge/Fog nodes, and Cloud computing. The need for intelligent control and decision at each level depends on the time sensitiveness of the IoT application.

. IoT-AI and WATER MANAGEMENT

Like I mentioned earlier too, the near future is more automated and sophisticated than manual and AI and IoT are one of its essential drivers which are related by this fact that the number of IoT devices increased 31% year-over-year to 8.4 billion in the year 2017, and it is estimated that 30 billion devices are expected to be ready by 2020. The global market value of IoT is projected to reach $7.1 trillion by 2020.

IOT and AI are extremely useful in water management

The main objectives of online water quality monitoring include measurement of critical water quality parameters such as microbial, physical and chemical properties, to identify deviations in parameters and provide early warning identification of hazards.

Also, the monitoring system provides real time analysis of data collected and suggest suitable remedial measures.

To be precise the three subsystems include:-

Data management subsystem includes the application which accesses the data storage cloud and displays the same to the end user.

Data transmission subsystem consists of a wireless communication device along with build in security features, which transmits the data from the controller to data storage cloud.

Data collection subsystem consists of multi-parameter sensors and optional wireless communication device to transmit the sensor information to the controller. All these subsystems include various sensors and tools to measure parameters viz. pH, DO, Oxidation reduction potential, temperature, turbidity , conductivity, water level sensing, conductivity, relative humidity, presence of organic compounds, chloride levels, etc.(2.)

For each parameter there are sensors

Sensors are connected to the controller, either directly using UART protocol or remotely using Zigbee protocol. The controllers are connected through GSM/GPS.

Advanced systems even have voice recognition AI that function on the basis of commands given through voice or respective smart phones. This simple yet advanced system gives real time measurements of above discussed parameters making water management most effective and easy.

. THE IMPACT

A simple example given in the previous section explains how effective this system is, and in case of water quality monitoring this IoT-AI combination is now adapted almost everywhere and almost every other water quality management technology has incorporated such systems into their technology.

As EHS managers or environment engineers this concept can do wonders if utilized precisely. We all are aware that ETPs have the three tier treatment system of primary, secondary and tertiary to treat our water. However, we are also aware how challenging it is to regulate and monitor the ETP and make it run smoothly.

We have to manage the flow rates, maintain pH levels, estimate CODs, BODs, nitrogen levels which itself take its own time and hinders in taking a quick decision.

Even MLSS management and monitoring of organic compounds is a tough nut to crack as we have to go through different tests to get things done. Management of Hydraulic loads and even estimation of DO in real time can be a challenge at times.

This IoT-AI combination can be of great help to us to manage our ETPs as it gives us data in real time and empowers us to control the ETP through our PCs or cell phones, no matter where we are.

The IoT-AI system for wastewater is similar to the quality management system with different levels.

Sensors for respective parameters of each levels are installed with their controllers in place, which are then interconnected and connected to the main controller, which is further connected to an AI device viz. PC or cell phones. Such systems give us facilities to monitor and control nearly all the parameters through one click or one voice command.

Even further advanced system have microscope connected to sensors as well as to monitor development of Bacteria and other microbes in biological tank in quick time.

. This system has immense positive impact on water management as it enables:-

Effective time management:- one of the biggest advantage is estimation of CODs and BODs in real time which usually takes time from hours to days. Even the flow rate management becomes easier to control and monitor.

Power saving:- Power saving becomes easier, for instance a common problem encountered by us is management of DO levels, and in order to manage them, we have to manage the aerators as well, also its estimation takes time . With this system involved, the aerators are functional as per the DO levels, for eg. if DO levels are high, the aerators of a particular section get switched off as signaled by sensors thereby, saving power in huge amounts. Similar application can be served for pumps to control flow rate and recirculation rates.

Manpower:- In order to maintain an ETP, manpower requirements are huge and in these tough times getting trained manpower is challenging. With IoT-AI in place, manpower requirements become very less as it empowers us to control ETPs even through our cell phones. This system also helps us run ETPs during holidays, shut downs or even in times of pandemic lockdowns.

Ensures safety:- Any malfunctioning or mishap can be easily controlled in one go , and even continuous exposure to effluent can be minimized.

Not just ETPs or STPs even lakes and oceans can be monitored, for example, The Ocean of Things project is a DARPA-led program designed to establish an Internet of Things across large ocean areas for the purposes of collecting, monitoring, and analyzing environmental and vessel activity data. The project entails the deployment of about 50,000 floats that house a passive sensor suite that autonomously detect and track military and commercial vessels as part of a cloud-based network.

. EASIER DESCRIBED THAN APPLIED

Although there is much effectiveness, the challenges related to this system are also many:-

Lack of interoperability and unclear value propositions:-

Mike Farley argued in Forbes that while IoT solutions appeal to early adopters, they either lack interoperability or a clear use case for end-users.

Privacy and security concerns:-

Since system runs on internet and wifi, these are vulnerable to potential cyber-attacks and data leaks.

Fundamentally there are 4 security objectives that the IoT system requires:

(1) Data confidentiality: unauthorized parties cannot have access to the transmitted and stored data.

(2) Data integrity: intentional and unintentional corruption of transmitted and stored data must be detected.

(3) Non-repudiation: the sender cannot deny having sent a given message.

(4) Data availability: the transmitted and stored data should be available to authorized parties even with the denial-of-service (DOS) attacks. (3.)

Conventional structure:- One of the biggest challenges, as our system is adapted to reactive measure and operations rather than proactive ones.

CONCLUSION

Overall the IoT-AI are the things of "near future" especially for water management as the problem of water is increasing day-by-day, necessity of setting up institutions and models of water management is increasing day-by-day, and it is practically getting very difficult to manage things conventionally. The system though in a nascent stage might prove to be a great breather to our entire water management universe, there are individuals putting their efforts day and night to ensure things are done right. Evolution is the tendency of nature as stated in the beginning of this article and this opportunity to evolve will make our near future much brighter and easier, making our systems simpler and less complicated and enabling us to live in a safer environment and make the world a better place to live.

REFERENCES :-

1) As per an excerpt from Deep Learning for IoT Big Data and Streaming Analytics: A Survey". IEEE Communications Surveys & Tutorials. 20 (4): 2923–2960.

2) Geetha and Gouthami Smart Water (2017) 2:1DOI 10.1186/s40713-017-0005-y.

3) Supriya, S.; Padaki, Sagar (2016). "Data Security and Privacy Challenges in Adopting Solutions for IOT.

IoT-AI Systems: the Near Future of Wastewater and Water Management

Sumeet Sharma

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