Smart Contracts & BlockChain: An Introduction to the Ethereum project

Since the world is currently riveted with the Paris climate accord, consider the following scenario: Sensors at various places collect the atmospheric carbon emission readings, and the countries who meet the emission standards are automatically credited with the carbon credits. Automatically is the operative word here. There will be no central authorization authority or a single enforcement agency, neither will there be human intervention. The entire process will be accomplished without the intervention of a third party, and with the help of a mechanism which seamlessly crosses international borders, and is not constrained by bureaucratic inertia.
This may seem far-fetched, but what you just read is a slight peek into a future enabled by Blockchain.
Blockchain, at its most abstract level, is a decentralized database with inbuilt consensus building mechanisms. Take your debit card transactions for example. Currently, they are enabled and secured by your bank. Every transaction is stored on your bank’s system, and the bank checks those transactions to update the balance of your account. You trust your bank to maintain everything. The blockchain is a total inversion of this centuries old paradigm. Rather than one ledger, in the hands of one entity, Blockchain is distributed across nodes, and each node has the record of all the transactions. Using Hashing and Public Key cryptography, it is ensured the record of transactions is immutable and available to all. Therefore, malicious agents can’t modify the transactions already done, making the system consistent, nor is there a single point of failure. The most well-known implementation of this idea is bitcoin.
This concept is truly revolutionary. Next-gen enterprises can leverage the power of blockchain to trigger actions based on automatic checks, ensure automated delivery of updated artifacts with inbuilt authentication. A Proof-Of-Concept already undertaken by Infosys utilizes blockchain in the manufacturing industry. A feature over the blockchain which is utilized in these scenarios is a smart contract. And a platform which enables this is the Ethereum project.
Ethereum comes with a programming framework, and a decentralized run-time environment called the Ethereum Virtual Machine or the EVM. To this decentralized “world machine”, folks can publish “code”. This code can encompass business logic and can contain routines to invoke other contracts. Ethereum framework charges people for the computing resources used for running those contracts on the virtual machine.The execution of these contracts will not falter in case one node goes down. Compare this with the traditional client-server architecture. If your bank’s server goes down, everything stops. Since Ethereum is decentralized, every node in the system has the copy of the contracts. Ethereum allows people to post smart contracts to its Blockchain network. Ethereum has been used to develop truly decentralized apps. The apps are not hosted on a server or connect to a hosted database, they run on a decentralized framework
Enterprises can use qualities of blockchain with some possible constraints in their solution implementations. While blockchain allows all nodes the access to the transactions, companies choose to run their blockchain networks on permission networks. Only a selected group of nodes are allowed access to transactions. Blockchains can ensure autonomous and speedy exchange of assets with minimal human interventions. We live in the age of automation, and enforcement of contracts remains one of the final remaining frontiers. Smart contracts can change that.

Predictive Analytics in Traditional Retail

The retail sector is one of the prominent sectors to use analytics for deriving insights so as to boost sales. With Google claiming that the focus is shifting from business intelligence to business analytics, the retailers are taking the pragmatic approach of storing and analyzing the humongous amount of data. The data being stored ranges from simple purchase order to customer data being pulled from social networking sites like Facebook and tweeter.
With the advancement in big data technology, it has now become possible to store and analyze data in the order of petabytes. Apart from deriving the KPI from historical data ( the classic case of BI) retailers are focusing more on deriving the insights and predicting the future events (Business Analytics or Predictive Analytics). Though the online retail stores like Flipkart and Amazon seems to be in the forefront of the action, retailers having the traditional business models have also started heeding towards business Analytics.
In a retail domain, the focus is more on increasing the sales by predicting the customer behavior rather than increasing the efficiency of product manufacturing and distribution by predicting the trends in demand and identifying the possible bottle-neck. Currently, there are a lot of commercial offerings in terms of a recommendation engine, which claim to increase the conversion rates multifold but there is the shortfall of offerings which address the problem of traditional retailers. Predictive analytics can be used in multiple ways to increase the efficiency and profitability of a business.
Analyzing the POS data for Better production and supply chain management – The point of sale data can be used to analyze the user preference for different products and their demands can be analyzed in real time. This data can further be used to predict the demand in future. This will help the manufacturer to plan the production and stocking of product efficiently. The problem of overstocking and nonperforming inventory can be minimized by predicting the future demands. One or more of the algorithm like linear regression, trend analysis, seasonality etc. can be used for prediction.
Having realistic sales target by forecasting the sales – By predicting the demand for various products, manufacturers can have realistic figures for sales and revenue. By predicting the sales, Sales target can be kept reasonable and practical to achieve. Predicting the demands of products in future can help bringing stability to the market. With realistic sales target, organizations can align their sales team to work efficiently and focus on emerging markets.
Analyzing the feeds from social media to engineer new products – Sentimental analysis is being used now a days to analyze the opinion of customers for any given product. This information can be used further to improve the product quality by fine tuning the product features so as to address the customer requirements in a better way. By clustering the products based on their features, new products can be designed with features having higher demands and acceptance. This can further reduce the cost of planning the product and its subsequent launch in the market. Various clustering and collaborative filtering algorithms are available to group the products having similar features. These algorithms are also used to predict the user preference which can be helpful for deciding the product features targeting a specific customer group.
Though the use of Artificial intelligence and machine learning in Bricks and Mortar stores seems to be a distant dream there use in the future is inexorable. Predictive analytics is a step forward in that direction.

Artificial Intelligence – in its Adolescence

Quoting Babak Hodjat words “A lot of what AI is being used for today only scratches the surface of what can be done. It will become so ubiquitous that we won’t even call it AI anymore.”
For the Nextgen to rewind and know that this form of me existed, I (AI)write this blog about my current phase –I call it, my late teens. It will not be too far before I grow up to be a complete adult and be the heart and mind of future systems. As you read, even without your knowledge, I could be in your pocket, telling if it’s worth reading the blog, giving you the percentage of accuracy, the connected blogs, and also the health implications based on the posture in which you are reading the blog.
Origin: It started with a group of scientists who wanted to build a human brain.With all due respect to John McCarthy – my Father believed that ‘every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it’. Telling in simple terms, I(a skeleton of wires and switches) was pushed into parrot or imitate a human – that was the beginning. I guess that’s how all humans learn, where child parrots the teacher/parent, but the real understanding creeps in later with experience. I was able to talk and play the game(chess) like humans.
Transition: Many call this asWinter phase and were almost a near death situation as investors backed off and I was not up to the mark. However,I was rejuvenated with the strength of Machine and deep Learning which meant that, for me to learn and simulate how a human behaves will first need a lot of data feed as to how a human behaves in such similar situation and then I build a pattern and relationships out of it over a period of time. Then onwards, my growth steadily has been streamlined into the “learning” and “problem solving” abilities.
Today’s Buzz: I am now at this stage where I am still not perfect and the more I am applied, the more I behave like a human. I attract a lot of buzz for my learning capabilities combined with the ability to predict and perform cognitive functions. Some of the top places where my siblings are already there are: Siri, Tesla, Alexa ( the list goes on) and in Banking – Chabot as financial assistance, risk assessors, fraud detectors, algorithmic traders and customer service recommenders are just a few to mention.
Overcoming the insecurities:

  • Globally I am there but I am still not there – sounds a little abstract but yes that’s the stage I am in. Everyone talks about me and understand (or rather seem to have understood)that I will make a difference but don’t yet know how I make that difference. Adding to it is the high initial cost of infrastructure and lack of required ecosystem which act as deterrents. So there is a cautious approach taken by most of the players and follow a wait and watch strategy.My take is: calculated risk takers will have an early mover advantage and be ahead in the competition.
  • Some of my masters who adapted me confuse me to my cousin RPA – Robotics –who is more of a rule executor wherein rules are predefined. However, I differ from the robot that I form the rules myself based on the historic data input and the model flows executed. To clear the confusion, we both complement very well.
  • Then there are those extremists who fear I will take over the human race. It’s fun seeing humans compete with me. Beat that fear, as I am like the Alladin’s Genie, how much every human like I try to become, I am still in a human’s hand to be tuned. I might take over some of the jobs, but humans have more time now for upskilling and explore newer jobs which require creativity, and jobs which need emotional intelligence, persuasion, social understanding and empathy (I envy humans here).

I, in a responsible collaboration with my trending tech family members, like Cloud technology (for affordable access), Big data(for analysis), Robotics(to execute automated tasks), Blockchain(by way of secured smart contracts), IOT(to connect machines) and Open source, am ready to service hand in hand with that leader of Vision, more to empower the human race than to overpower them.

The Chicken and Egg story: Unreasonable demands on a Vendor and Failed promises of an Employer

The other day, a client of mine called me up and sounded quite livid at a high profile fintech company. His son passed out of the college a few months back and was offered a lucrative job by this fintech startup. After about 4-5 months of frequent shuffling across stop-gap work and training, he was asked to quit. On the other hand, his other friends who were not as ‘lucky’ as he was in the college placements and got just passable openings with other companies were in a better position as they did not face any such threat as yet.
My client was devastated emotionally and wanted a shoulder to cry on, perhaps. He felt that the Indian IT companies were playing with the careers of the youth. These companies mismanage their work; they overestimate their business projections for short-term gains; they hoard the best possible students from elite colleges without having enough business in hand and then leave them in the lurch.
While I empathized with him, I did not want to take the complete blame on my community of IT companies. While it may sound too cruel, I thought it was my opportunity to speak out and give him a chance to correct himself – when he negotiates a deal with me the next time.
After listening to him patiently for about 15 minutes, I took him back to a recent transaction that we had. I reminded him of the project wherein after a year-long negotiation and after keeping me on tenterhooks for all through that period, he finally gave his nod to start the project. And as he issued his purchase order, he wanted the project to start within a week’s time. And then what did he do when I could not put up a team within that short time? He escalated the matter to my COO. That indicates that he expected me to keep the team with me without any gainful work.
I explained to him as to how the evaluation process goes on for an excessively long time without any clarity on the closure. The vendors keep building and releasing their teams assuming the start of a project, which remains elusive. Some established players are able to carry this weight of unproductive workforce for a long period but a few smaller vendors end up burning their reserves on this unreasonably long wait. The employer of his son would be one such company suffering at the hands of his own community.
A good practice followed by the professional companies is to plan their business well in advance. As the highly ambitious revenue projections come in for the following year, the recruitment planning too starts. In order to outdo their competitors, these companies make a beeline to the graduate schools at the earliest. So much so that the candidates get recruited almost a year before they complete their course. And then, if the business projections don’t add up for some reasons, the process breaks down. It starts with delays in offer letters; even if on boarding happens, it ends up in a painful separation after a short while.
So, the entire system has deteriorated over a period. The corrections are required on multiple counts. As the apex body of software companies in India, NASSCOM should take some responsibility to bring in behavioural corrections, I suppose. It is best to induce self-restraint rather than expecting an external intervention.
Can the clients engage these software companies to be more reasonable with their demands? Will they bring in more transparency on their expenditure budgets? Will they refrain from making up for all their delays with unreasonable demands on timelines for delivery? Could these Individuals grow above their conceited considerations? Will the Education Department issue a guideline against entertaining campus interviews so much in advance?
Or whether the NASSCOM can issue a guideline to the member companies to refrain from early recruitment. With seasoned professionals managing these member organizations, I am sure they do not need a RERA like regulatory framework. For, the problem is not much different from that. Recruiting a year in advance, without a clear visibility of the business, is in a way comparable to the ‘pre-launch’ irregularities of the real estate sector that RERA has tried to arrest.

IoT – is that the most ubiquitous idea since the invention of wheel?

The current technology landscape is replete with some very exciting concepts, a stack of over-hyped terms and a few genuine innovations. Call it Artificial Intelligence, Cognitive Computing, Data Analytics, Data Science, Blockchain, Bitcoin, Cloud Technologies, IOT and the list goes on. Amongst all these concepts, the Internetworking of Things (IOT) is one exciting area of work that sans any boundaries and has the potential of touching every existing life on this planet.
IOT combines multidisciplinary technology and can provide essential feed to rest of the buzzwords mentioned above. Amongst the five sense organs of the human sensory nervous system, we have attained great success in replicating the senses of Sight, Hearing and Touch. And these form the backbone of the successes achieved interconnecting devices. There is a lot of work happening on the remaining two senses of Smell and Taste. Once done with, the technology would have measured the most fascinating and the most intriguing creations of nature.
The rapid growth in the field of sensors and actuators has immensely helped the growth of IOT as well. We have already seen many commercial products in the market that make use of interconnected devices. From the basic equipments with automated thermostats to intelligent lighting systems. From distant monitored air conditioners and electric geysers to remote controlled surveillance and security systems. Smart Homes are the latest offerings in the market place now. From heavy commercial machines to personal wearables. All of these modern gadgets are now commercially available and have contributed to the successful industrialization of IOT.
The manufacturing sector has seen immense growth in the area of IOT. The use of robotics and automation of manufacturing processes depend heavily on transfer of information across components monitoring smaller sub-processes. The quality controls are governed by parallel but connected monitoring component devices. Besides, a smooth and efficient manufacturing cycle depends heavily on timely availability of raw materials and optimal stocking of inventories. The entire inventory management system depends heavily on interconnected devices keeping a close measure of these inventories.
One of the best examples of usage of IOT in the service of humanity that I have seen is perhaps a case study on tracking the movement of diamond miners in South Africa. Many of these mines, hundreds of meter deep below the surface, run the risk of miners losing their lives due to various work hazards. Often, the controlling teams do not even get to know the status of these teams working deep below the ground. The IOT developments have ensured a sensory communication mechanism that continuously tracks the movement of miners and at the very first clue of any lack of movement in the mine, the standard operating procedure for rescue operations are invoked without any loss of time. Such a system with interconnected devices can go a long way in improving the working conditions and lowering the risks of mine workers.
Usage of IOT has also gone up in the financial and banking industry. Various financial transactions going through connected cars are becoming common now. Be it an automatic collection of toll-fee or the payment at fuel stations, the identity of the customer is being established through connected devices. With wearable devices, the financial industry gets to collect humongous amount of data to establish the various patterns of their clientele. The analytics across these data points help in detecting and blocking any potential fraudulent transactions as well as giving a dope on offering the right kind of products for different client segments.
With the giant strides taken by the industry on IOT, I am sure in no time we will have devices measuring human emotions. And then, when you read through this blog, you may not have to consciously push your fingers to the ‘Like’ button. The wearable on your wrist will automatically gauge your emotions, connect to your device on Bluetooth and that in turn will do the honours seamlessly.

Allay Your Fears of Automation

Automation is a popular buzzword these days. Every organization and every leader are talking about automating something or the other. In the quintessential IT services industry, this buzzword is projected as the panacea for all the growth pangs that it is going through now. On the other hand, this term also instills a certain degree of fear amongst the lower half of the organizational pyramid. They see it as a threat to their jobs.
From an impact perspective, we see two types of automation. One, which facilitates foray into a new uncharted territory and hence does not impact the workforce. The second is something that replaces an existing manual work and hence is a cause of concern for the people.
Consider the case of a common passenger elevator that we see in every multi-story residential apartment and in offices. This one automation has not replaced any manual system and on the other hand, has opened up a huge construction industry resulting in enormous vertical growth of the real estate across the globe resulting in a USD 8.5 Trillion business as of last year.
In the Banking Industry, despite the fast paced computerization over the last 15 years and given the fact that over 50% of the customers carry out a bulk of their transactions over the Internet, the number of employees has only gone up. In India alone, the number of Bank employees have grown to about 1.3 Million and this does not include the host of allied agencies who outsourced a major chunk of regular offline Banking transaction by the Banks.
Some 25 years ago, Indian Banks were struggling with manual ledgers for their account keeping. The branches would have a dedicated workforce to only balance their books as of the end of each month. It used to be an ongoing work all through the year. Post automation, this need for balancing had gone but it also opened up many new areas of work. The other day, a colleague of mine was narrating an incident. He was in another city on a personal trip and did a high-value purchase one late evening at a mall. And as he was entering his password at the POS terminal, he got a call from his Bank checking if he was indeed making that payment – as this was a different city and the value was much higher than his normal pattern. Could we have imagined this a few years back? We neither had such intuitive data points nor did we have a central, online, 24×7 system. So, while automation took away a nature of the job, it created some other avenues of providing better and secure service to the customers.
Therefore, while it may appear, in the short run, that automation might take away someone’s job, it is clear from the data points above that it is only the nature of job that changes and it is the Darwinian theory of natural selection that creates and finds a suitable alternative employment for the active workforce.
In the IT industry, the workforce is concerned about automated coding, automated testing etc. It is a fact that the IT industry has matured to a state where it can indulge into automated coding, though at this stage, it is only to a limited extent. However, it is a process of evolution. Like we still have buildings without an elevator, we will still have a piece of code or a test case that will be written and executed manually. It will follow a process of evolution and by the time automated coding and testing is all permeating, we will have workforce finding its way through the Darwinian ‘natural selection’ towards new vistas of opportunities.
The only difference between the Darwinian theory of evolution and today’s advancement on automation is that it was a slow process that was theorized in posterity. But automation is our chance to define the scenario for posterity. Think big and think fearlessly. It may take the time to mature. Like someone thought of a tunnel boring machine in the 19th century and only now we see that as an essential tool to build modern underground transportation in a busy town. The process of evolution and the mechanism of natural selection are both slow and they allow you enough time for transition.

The Hyped Blockchain Can Provide much-needed Fillip to Automation

From a suspicious and skeptical currency alternative to a quintessential business tool that could bring down the cost of operations, with lightning speed and unswerving trust, has been the journey of Blockchain, as a concept and as technology, over the last couple of years. So much so that every industry, every organization and every CEO wants to be associated with Blockchain, to be seen as a pioneer.
The blockchain is a largely distributed ledger that is self-certifying, is not owned by anyone in particular and is supposed to be incorruptible and immutable. It guarantees the validity of every transaction with no scope for errors – be it omission or commission. There are numerous other hyperbolic prologs written on Blockchain. But I am yet to see a convincing epilog on that.
But I am convinced on one thing. This is a great opportunity to dovetail the other greatly anticipated revolution around automation. For, in order to make a success out of Blockchain, there is a huge dependence on automation. The more we automate our mundane tasks, the more we create opportunities for that self-regulatory, self-certifying, self-executing protocol of Blockchain.
Let us take a very simple example of the settlement of travel claim for an official trip. Imagine a situation where the organization sets a policy of prescribing the use of certain specific cab agencies like Ola and Uber, who maintain a real-time online network. And the organization mandates to use a certain food chain that provides a central connectivity to its database. The Airlines operations are, in any case, completely digitized. But all these agencies have no inter-connectivity. Can Blockchain bring these distinct organizations together to provide a fast, straight through, secure chain of transactions for me?
Now imagine, I take an official trip by one of these airlines, use a cab to reach my hotel and then to a few client locations, have my lunch at one of the prescribed food joints and return to my base the next day. As I get off the cab at my apartment gate, I press one icon on my official phone that confirms my trip closure. It spans a transaction on the Blockchain that hits the servers of the airline, the hotel, the cab agency and the restaurant. My organization id and my employee id is the key. The servers pick the data over the last 2 days, stamp their confirmation with value on the Blockchain and as I reach my 9th-floor apartment, unpack my bag, freshen up and hit the bed, I get a ping on my phone – my travel settlement has been done. All these players were bound by a smart contract indeed.
If the scenario described above can be a reality, then the focus is bound to shift on automation. There will be more hotels – beyond the realm of 3 and 5-star chains, who will automate their systems. There will be more of the smaller cab agencies – beyond the empire of Ola’s and Uber’s, who will automate their operations and put up their data for public access. And there will be more restaurants, who would want to publish their transactions onto a central server.
And that opens up a plethora of opportunities for automation. While the large businesses will be able to automate their systems on their own, the smaller ones will open up a new cloud-based business opportunity for IT players and start-ups, as service providers, to deliver systems that will not only be accessible from the external world but will also be Blockchain compatible.
So, even if there are apprehensions on the ability of Blockchain technology, in a short run, to bring together varied applications across diverse business functions to facilitate an efficient business transaction. It surely will, in the process, push through the automation agenda of the IT industry to achieve a reasonably high degree of success on that count at least. And the Blockchain might just follow.

IOT – Possible uses to make our life easy

The Internet of Things may be a hot topic in the industry but it’s not a new concept. In the early 2000’s, Kevin Ashton was laying the groundwork for what would become the Internet of Things (IoT) at MIT’s AutoID Lab. Ashton was one of the pioneers who conceived this notion as he searched for ways that Proctor & Gamble could improve its business by linking RFID information to the Internet.
At a very basic level, “Internet of Things” means devices that can sense aspects of the real world — like temperature, lighting, the presence or absence of people or objects, etc. — and report that real-world data, or act on it. Instead of most data on the Internet being produced and consumed by people (text, audio, video), more and more information would be produced and consumed by machines, communicating among themselves to (hopefully) improve the quality of our lives.
IOT describes a system where items in the physical world, and sensors within or attached to these items, are connected to the Internet via wireless and wired Internet connections. These sensors can use various types of local area connections such as RFID, NFC, Wi-Fi, Bluetooth, and ZigBee. Sensors can also have wide area connectivity such as GSM, GPRS, 3G, and LTE.
The classic example is a smart refrigerator that can read RFID tags on grocery items as they’re put inside, then look up those tags via the Internet to identify milk, eggs, butter, and those four frozen pizzas you just bought. The fridge tracks usage, then — cue trumpets! — alerts owners when they’re running out of groceries, or need more food since people are coming over to watch the game this weekend. (The fridge can tap into your calendar, of course). The refrigerator could even place a grocery order automatically (perhaps delivered via Amazon Fresh). Similarly, that smart fridge could warn about products nearing (or past) their expiration dates.
The Internet of Things concept lends itself to fantastic ideas. What if your house could save you effort by recognizing that you’re at a drugstore and automatically sending a list of things you need? Stuck out of town on a business trip? Tell your house to stay in vacation mode, turning lights on and off to make the place look lived-in, but not running up heating and cooling bills.
Device-to-device communication creates other possibilities. Simple motion sensors can detect people moving around the house, turning lights on and off, opening or closing blinds or drapes, or even adjusting the temperature. This functionality is already so refined that many sensors are reasonable “pet immune,” so dogs and cats don’t trigger automated functions.
If these “smart home” ideas seem familiar, it’s because many are on the market — they’re just not commonplace. One well-known example is the Nest thermostat (now owned by Google). It adjusts heating and cooling based on usage patterns and even billing rates and can be controlled from a mobile app. Similarly, smart appliances have been around for years, not just refrigerators, but washing machines, heating and cooling systems, lighting, and dishwashers too.
If there are so many smart devices, why aren’t we all living in the home of the future? From much other reason, one reason is that home appliances don’t turn over at the same rate as smartphones, tablets, or even PCs. People don’t replace refrigerators and other home appliances very quickly. Tablets may have killed off netbooks in just a few years, but it will take far longer for smart appliances to migrate into many people’s lives. Other Reason may be that the “Internet of Things” brings a multitude of privacy and security implications.
You can see many other Appliance like smart switch means you can control your bulb, Television, fan etc. with the help of smartphone via Wi-Fi or Bluetooth. According to me, we can use this IOT concept for the ambulance to reach the hospital as soon possible. if we make our ambulance smarter so that it can send its location and destination to nearby traffic police so that Traffic police make rout clear in advance and help to reach a destination on time.
Using Internet technology to make our homes and devices smarter is easy to understand, but is also a very large endeavor that will take a lot more time — after all, we’ve already been at it over a decade.

IOT & Drones in Indian Agriculture

Agriculture, a sector that provides work to more than half of the country’s population, contributes less than 1/5th to its GDP. This is primarily because of the uninformed decisions taken at various stages of cropping by farmers.
Farmers across the country depend more on the practices learnt by their ancestors and take various decisions based on myths.  They have a belief that anything for improving soil fertility must have a direct response and the more they add it, the better things should become. Same is their concept regarding fertilizer use. Unaware of heating, they add more and more fertilizer in hope of better yield and end up burning the roots. Also, what the soil lacks and what kind of fertilizers should be used is not known to them many a times.
Now, the time has come to switch from traditional methods to technological methods. Drones are part of the solution. But, when combined with Internet of Things (IoT), it can lead to major breakthroughs in agricultural development. Internet connected drones can help the farmers in the following ways.

  • Soil analysis: Before start of the crop cycle, they can produce precise 3-D maps for early soil analysis, useful in planning seed planting patterns. After planting, drone-driven soil analysis provides data for irrigation and nitrogen-level management.
  • Planting: They can shoot pods with seeds and plant nutrients into the soil, providing the plant all the nutrients necessary to sustain life.
  • Spraying: They can scan the ground and spray the correct amount of liquid with even coverage. This will be five times faster than traditional methods.
  • Monitoring: Vast fields and low efficiency in crop monitoring together create farming’s largest obstacle. Drones can show precise development of a crop and reveal production inefficiencies, enabling better crop management.
  • Irrigation: Drones with hyper-spectral, multispectral, or thermal sensors can identify which parts of a field are dry or need improvements.

But generally when we talk about drones everyone thinks a remote controlled device. But what if we can move it up to the next level. To increase the performance even further Drones can be connected with satellite, IOT and AI instead of remote control. We can take the image of our field from the satellite and store it in our drone. Then the movement of drone can be controlled by the satellite to make sure the drone covers the complete field and does not go beyond the marked field. Satellite will give line of movement for the drone and will make sure the drone moves only inside the field.
Furthermore we can integrate the spectral information and also the position and the shape of the plants in the software so that it can perform a scan and detect those ones that are weeds. Farmers can then apply weedkiller to specific areas, monitor the evolution of their crops over time.
Apart from agriculture, internet connected drones can be used in many other fields such as in mines, search and rescue operations, delivery of goods, in zoos to monitor wildlife, in seas to track disasters beforehand, etc.
The individual applications of IoT as well as drones are many. And, now there is a need for both the technologies to identify their capabilities they can provide to each other and become an integral stepping stone for one another. This as a result can lead connected IoT drones towards a better future for all.

Image Recognition: The Eye of Artificial Intelligence

AI and Automation are synonymous with automating human tasks and bringing in human-like intelligence in systems. However, Image Recognition, one of the most important and significant components in AI is like a human eye for AI.
How can I know whether the driver driving a vehicle is tired or frustrated? How do I know the Best driving speed for all vehicles and when is my vehicle tire to be replaced? An Image Recognition system can help solve all these problems.
Let me first define Image Recognition. Image Recognition is the ability to process and identify images and patterns in pictures and Videos. This allows a system to recognize different types of objects in pictures. Some of the Image recognition systems are listed below:

  • Optical Character Recognition (OCR)
  • Pattern Matching
  • Face Matching
  • Feature Matching
  • Motion Detection
  • Traffic Signal detection
  • Video Surveillance

Image Recognition systems apply Machine Learning algorithms to analyze the data in images. Each Image pixel is labeled with Y, U, V color entries. Decision Trees, Artificial Neural Networks (ANN), Instant-Based Learning, Scale Invariant Feature Transform (SIFT), Eigenvector and Support Vector Machines algorithms are used for image recognition and classification of image data.
Image Recognition would be most useful in Industrial Automation, Video / CCTV surveillance systems, Home Automation Systems, and Healthcare. Maintenance operations in Industry involve close monitoring of Equipment and Plants. Image Recognition systems can analyze the videos and images of Plants and Equipment and identify potential breakdowns & security hazards. Equipment that is damaged or is due for repair can be quickly identified by pattern recognition feature of Image Recognition systems.
Video surveillance systems involve scanning videos recorded to identify people, images or objects. This can be easily automated by an Image Recognition system. Image Recognition systems can continuously identify people from Images and recognize faces and objects, just like a human eye. The video analysis can be used by Insurance companies as well. Image recognition can be used Home Automation system to identify potential thefts, unwanted intrusion, and alert about potential hazards.
Smart Cities requires monitoring and surveillance of large public spaces such as Roads, Parks and Parking etc. Image Recognition helps in the surveillance of public places. Image Recognition system can quickly identify the types of vehicles on the road, alert about accidents, hazards and traffic conditions.
Image Recognition, when applied to Medical images, can help quickly identify diseases and check the health of patients. The pattern of organs and diseases along with past data also suggests a possible diagnosis of patients. The potential for Image Recognition is limitless. It is required in IOT Applications and Digital Farming.
OpenCV, Amazon Recognition, Google Video Intelligence API, Google Cloud Vision API, Microsoft Cloud Vision API and Microsoft Emotion APIs are some of the Tools that provide basic and advanced Image Recognition capabilities. These tools can certainly provide human eye like the capability to AI systems.