The Ministry of Railways adopted radio frequency identification technology

Custom RFID Kerfob, RFID Tag, For Pet Management, Hotel Management, Acce...

What is RFID?

Can RFID detect location?

UHF systems can typically tell you that a tag is within a defined read field, but not specifically where within that field. Mojix, for example, uses a phased-array antenna system to locate passive tags in three-dimensional space, usually to within about 3 square feet.

This is not a simple question to answer without knowing more about what you are specifically trying to achieve, as well as the nature of the environment involved. Many considerations must be made when choosing the proper radio frequency identification system—and, as in most situations, there are often trade offs. One solution might offer greater location accuracy than another, but at a greater cost. That said, I’ll try to answer your question as best I can.

Generally speaking, an active ultra-wideband (UWB) RFID system will be able to determine where a tagged object is located to within a few inches. UWB tags can be fairly expensive, however, so if you are tagging a large number of objects, the system could become costly.

A passive ultrahigh-frequency (UHF) RFID solution will provide about 15 to 30 feet of read range, depending on which tags and readers you deploy, as well as other factors. UHF systems can typically tell you that a tag is within a defined read field, but not specifically where within that field. Given that many applications require you to know where a tag is located in the read field, some companies have developed solutions that deliver greater location accuracy.

Passive systems utilize something called a Received Signal Strength Indicator (RSSI) to determine how close an object is to an RFID interrogator. RSSI can’t tell you that a tag is, say, 8 feet 11 inches from the reader, because signal strength can be affected by waves bouncing off the floor or ceiling, but it can tell you that a tagged object is getting closer or further away. So the RSSI for an object closer to the reader within the same environment should be stronger than for one located further away. However, it would be difficult to distinguish the difference in location of tags spaced an inch apart.

RFID near you

Despite these concerns, others say there are huge benefits to using RFID.

“At least 30 million people carry an RFID tag on them every day in their car keys or in their access control card to get into their office building or to buy gas or to pay a toll,” wrote RFID Journal’s Roberti. “Everywhere RFID has been rolled out in the consumer environment, consumers have overwhelmingly embraced it.”

One new consumer application is in credit cards. Consumers could simply wave a credit card containing a passive chip at an RFID reader to pay for their purchases.

While there is concern that hackers could remotely read the card information, supporters argue it would be easier for merchants, and the speed of the processing time could shave off more than a dozen seconds per transaction, which would add up. They also say transactions would be no more or less secure than they are today.

“That is, if you buy stuff today with a credit card, that information is stored in a database,” Roberti wrote. “When or if RFID is used to record sales, data will go in a database, the same one in fact. If the government wants access to the RFID data or the bar code data, it’s essentially the same thing.”

The controversy and discussion about RFID technology will not end anytime soon. But both sides agree that a sizable dose of debate is needed to hammer out the kinks. Meanwhile, the technology is appearing in an increasing number of places — though even if you look around, you still might miss it.

More info at http://www.asiarfid.com/blog/can-rfid-detect-location.html

RFID Warehouse Management Process, Outbound Process, Inventory Process, ...

How does RFID work?

RFID belongs to a group of technologies referred to as Automatic Identification and Data Capture (AIDC). AIDC methods automatically identify objects, collect data about them, and enter those data directly into computer systems with little or no human intervention.

RFID methods utilize radio waves to accomplish this. At a simple level, RFID systems consist of three components: an RFID tag or smart label, an RFID reader, and an antenna. RFID tags contain an integrated circuit and an antenna, which are used to transmit data to the RFID reader (also called an interrogator). The reader then converts the radio waves to a more usable form of data. Information collected from the tags is then transferred through a communications interface to a host computer system, where the data can be stored in a database and analyzed at a later time.

Tag Antennas

Tag antennas collect energy and channel it to the chip to turn it on. Generally, the larger the tag antenna's area, the more energy it will be able to collect and channel toward the tag chip, and the further read range the tag will have.

There is no perfect tag for all applications. It is the application that defines the tag’s antenna specifications. Some tags might be optimized for a particular frequency band, while others might be tuned for good performance when attached to materials that may not normally work well for wireless communication (certain liquids and metals, for example). Antennas can be made from a variety of materials; they can be printed, etched, or stamped with conductive ink, or even vapor deposited onto labels.

Connectivity Devices Identify, Locate, Authenticate, and Engage Endpoints

RAIN RFID readers and gateways are devices that power and communicate wirelessly with tags and deliver tag data to operating-system software. Connectivity devices communicate bi-directionally with endpoints that are within their field of operation, performing any number of tasks including simple continuous inventorying, filtering (searching for tags that meet certain criteria), writing (or encoding) selected tags, etc.

Connectivity devices can identify and locate more than 1,000 items per second. Readers can be stationary or mobile and use an attached antenna to capture data from tags. Gateways integrate stationary readers with scanning antennas to locate and track tagged items. Reader chips and modules are designed for to be embedded in applications like handheld readers, smart vending machines, automotive tracking, mobile devices and more.

Stationary readers require an antenna that sends power, as well as data and commands to endpoints. Since these readers are often used in automated applications they can support additional connections to external presentation sensors or light stacks to notify users of completed reads. Readers and gateways are connected to a host PC or network to transmit all of the tag data.

Reader Antennas

RAIN RFID readers and reader antennas work together to read tags. Reader antennas convert electrical current into electromagnetic waves that are then radiated into space where they can be received by a tag antenna and converted back to electrical current. Just like tag antennas, there is a large variety of reader antennas and optimal antenna selection varies per the solution's specific application and environment.

The two most common antenna types are linear- and circular-polarized antennas. Antennas that radiate linear electric fields have long ranges and high levels of power that enable their signals to penetrate through different materials to read tags. Linear antennas are sensitive to tag orientation; depending on the tag angle or placement, linear antennas can have a difficult time reading tags.

Choice of antenna is also determined by the distance between the RAIN RFID reader and the tags that it needs to read. This distance is called read range. Reader antennas operate in either a "near-field" (short range) or "far-field" (long range). In near-field applications, the read range is less than 30 cm and the antenna uses magnetic coupling so the reader and tag can transfer power. In near-field systems, the readability of the tags is not affected by the presence of dielectrics, such as water or metal, in the field.

In far-field applications, the range between the tag and reader is greater than 30 cm—and in fact can be up to several tens of meters. Far-field antennas utilize electromagnetic coupling and dielectrics can weaken communication between the reader and tags.

More info at http://www.asiarfid.com/blog/how-does-rfid-work.html

How can Wristbands add fun and purpose to your Event or Promotion?

We have already discussed the serious or critical part of having Wristbands for your events or promotions at length; you may have understood that having ID Tags and Wristbands are a great way to increase the security level of your event or promotion with an easy and almost fail-proof system. In this rather short blog, let us talk about the fun aspects of wearing a Wristband on events, charities and promotions.

Wristbands are the latest fad: colourful, cool, collectible, customisable, hi-fi and trendy. They make great fashion statement. Any better way to show appreciation for someone who donates and shows support for charity or a cause other than handing him or her with a wristband? Not just for the mega party charity events, Wristbands are fun for smaller fundraising groups and online communities too!

With Wristbands, you no longer have to deal with messy ink stamps or a tacky ID card strung around your neck like the metaphorical noose it is! Not anymore! Wristbands are cool and conspicuous. They can also be given different colour coordination, i.e., any number of layers of access relating to a single event can be added with different colours and materials that will add to the security levels.

Wristbands are best when it comes to keeping your child safe and secure at the pool, beach or camp-site, lest the panic of temporarily losing your child can be stressful and scary.  And also, you never know when your child would get distracted in an environment they love to play and be in. Your child wearing a wristband will help him or her reach safely back to you. Plus, with colourful options, it is easy to convince your child to wear Wristbands.

Because our Wristbands are highly durable and tamper-proof, they are ideal for longer period of use.  Providing a high level of security, they allow for on-site printing, if any customization is required ‘on the go’. Our Party Wristbands simply look great and make a great memento for everyone involved. Simply get in touch with us, order your fun Wristband, and add a bit of ‘wow’ and an extra layer of security to your event or promotion.

More wristband info at http://www.asiarfid.com/RFID-Wristbands/Paper-Wristband

Will Artificial Intelligence in Healthcare Support Physicians or Replace them?

Let’s ask ourselves a question, ‘Are we ready for a machine takeover in several areas of life, including healthcare?’ It is not possible to answer this question straight forward without imaging a futuristic scenario. Let us board a time machine and travel 10 to 12 years ahead nearing the year 2030. Suppose you are experiencing intense pain in your left arm – would you diagnosed by a physician or an artificially intelligent machine?

Artificial Intelligence in Healthcare: Adaptive Intelligence 

The idea of artificial intelligence in healthcare that eliminates the need of doctors, healthcare physicians, nurses, caretakers and other stakeholders is likely to be much more subtle. Experts see a lot of potential in AI and believe that this technology would support physicians rather than replacing them in the future.

Technology experts are always at the forefront of sufficing the needs of healthcare industry and patients through extended capabilities of AI. Such kind of intelligence that assists doctors in delivering the best possible care is known as adaptive intelligence.

Demystifying Machine Learning and AI in Healthcare 

Let’s dig deeper into what is machine learning and AI to later understand its relevance in healthcare domain. For many people, the term ‘artificial intelligence’ draws an imaginary image of humanlike robots. However, AI goes much beyond its usage through robots. The power of AI can be utilized through any device – as simple as a smartphone.

Artificial Intelligence is a computer science that develops programs to mimic human intelligence. The level of intelligence may range from recognizing patterns in data to deriving insights for problem solving.  This program based on AI capabilities can be implemented through a robot, smartphone or any other device.

Machine Learning is yet another term that is simultaneously used with AI. This technology helps in making sense from large amount of data by identifying and detecting patterns from it. This technology is currently used by Google to suggest terms based on your past searches. Even Netflix uses Machine Learning algorithm to provide you personalized suggestions based on history and the latest trends.

These examples only show how AI and ML are helpful to fulfil the needs of the users. Similar is the case of usage of Artificial Intelligence in Healthcare, i.e. it provides a helping hand to maintain the perfect balance in the healthcare ecosystem.  

The Helping Hand of Artificial Intelligence: AI Solutions for Healthcare

Healthcare professionals including doctors and other medical practitioners face the challenge of handling large amount of information of patients. They are constantly under the pressure of using the right diagnosis method and selecting the best treatment plan for each visiting patient, which might be in the range of hundreds per day.

For example, let’s consider the case of radiologist that use imaging techniques such as MRI, CT and X-rays to diagnose the injury of patient. Considering the large number of patients approaching radiologists for their injuries, the specialist is left with very little time to study each image or report. Radiologist also needs to study individual case with respect to studying patient’s medical history and current situation.

The problem of radiologists is to handle too much data in short time. This is where Artificial Intelligence can help. It is possible to program machines that scan these medical images to analyse whether they point or do not point towards a disease. At present, there are machine algorithms developed by Stanford researchers to identify pneumonia from images of chest X-rays.

However, this does not mean that radiologist would not be needed anymore. The technology of Artificial Intelligence and Machine Learning are providing a helping hand to maintain a balance in the ecosystem, but not replacing physicians or any medical practitioners. AI solutions for healthcare are aimed to make doctors’ lives easier and improve patient experience. This adaptive intelligence technology is helping doctors to serve patients through extended capabilities.

Though the concept of ‘Artificial Intelligence in Healthcare’ does not necessarily portray an image of robot with the white coat, it surely speeds up the workflow of doctors by supporting them with relevant insights. AI programs reduce the repetitive work of doctors, thereby giving more time to doctors for studying your case. The role of AI in healthcare continues to evolve and act as a personal assistant of doctors, but does not replace them.

More new information at http://www.asiarfid.com/blog/will-artificial-intelligence-in-healthcare-support-physicians-or-replace-them.html

60 Percent of India's GDP will come from AI, and other digital services by 2021

India is clearly on the digital transformation fast track,' says Anant Maheshwari, president, Microsoft India.

By the year 2021, around 60 per cent of the country's Gross Domestic Product (GDP) is expected to be derived from digital products and services. Created through the use of technologies such as Artificial Intelligence (AI), the Internet of Things and cloud computing, among others.

So says a study commissioned by information technology major Microsoft. It says digital transformation will add an estimated $154 billion to our GDP by 2021. "India is clearly on the digital transformation fast track," says Anant Maheshwari, president, Microsoft India.

Organisations, he said, are increasingly deploying emerging technologies such as AI and that will accelerate this change-led growth even further, with the application of this in sectors such as education, health care and agriculture. "(Such) Technologies can really solve some fundamental problems and if applied the right way, could unlock a lot of potential," Maheshwari told Business Standard.

The catch, he says, is the need for a supportive framework in place that allows free and fair use of such technology.

To illustrate, he said Microsoft had applied AI in Andhra Pradesh schools, where the government wants to address the issue of high numbers of students exiting in class 10. "About 25 per cent of students drop out at 10th standard. If you can use AI to predict and identify why students want to drop out, you can pro-activel engage with the students or their families to keep them back in school...you can do so much for the economy," he said.

Similarly in health care. "Technology can play a role in providing facilities like preventive health care and augmented diagnosis to the needy. Then, there is agriculture, where productivity can be increased by 20-30 per cent, simply by using predictive technology."

The central government has formed a committee on AI to suggest a technical framework or platform for the emerging technology. It is chaired by P P Chakraborty, a professor at IIT, Kharagpur, and has representatives from Google, Microsoft, NVIDIA and TCS. Also, from Nasscom, the apex association of the information technology (IT) sector, beside the National Informatics Centre and the ministry of electronics and IT. Its recommendations are expected by the end of this month.

More info at http://www.asiarfid.com/blog/60-percent-of-indias-gdp-will-come-from-ai-and-other-digital-services-by-2021.html

Comparison between Data Science vs Artificial Intelligence vs Machine Learning vs Deep Learning

1.Objective

In this blog, we will discuss Data Science vs Artificial Intelligence vs Machine Learning vs Deep Learning. Also, will discuss each of these individually for better understanding.

2. Comparison between Data Science vs Artificial Intelligence vs Machine Learning vs Deep Learning

a. What is Data Science?

R Data science includes data analysis. It is an important component of the skill set required for many jobs in this area. But it's not the only necessary skill. They play active roles in the design and implementation work of four related areas:

Data architecture

In data acquisition

Data analysis

In data archiving

b. What is Machine Learning?

Generally, there are 3 types of learning algorithm:

a. Supervised Machine Learning Algorithms

To make predictions we use this machine learning algorithm. Further, this algorithm searches for patterns within the value labels. That was assigned to data points.

b. Unsupervised Machine Learning Algorithms

No labels are associated with data points. Also, these machine learning algorithms organize the data into a group of clusters. Moreover, it needs to describe its structure. Also, to make complex data look simple and organized for analysis.

c. Reinforcement Machine Learning Algorithms

We use these algorithms to choose an action. Also, we can see that it is based on each data point. Moreover, after some time the algorithm changes its strategy to learn better. Also, achieve the best reward.

c. What is Deep Learning

As Machine learning focuses only on solving real-world problems. Also, it takes few ideas of artificial intelligence. Moreover, machine learning does through the neural networks. That are designed to mimic human decision-making capabilities.

Machine Learning tools and techniques are the two key narrow subsets. That only focuses more on deep learning. Furthermore, we need to apply it to solve any problem. That requires thought- human or artificial.

Any Deep neural network will consist of three types of layers:

The Input Layer

The Hidden Layer

The Output Layer

d. What is Artificial Intelligence

Basically, Artificial intelligence is a very broad term. Also, it is an attempt to make computers think like human beings. Moreover, any technique, code or algorithm that enables machines to develop. Also, behaviors falls under this category.

As we must be aware that an artificial intelligence system can be as simple as a software that plays chess. It doesn't matter how complex the system, artificial intelligence is only in its nascent stages.

3. How Does Data Science Relate to AI, ML & DL?

Data science is an inter-disciplinary field that has skills used in various fields such as statistics, machine learning, visualization, etc. It is general process and method that analyze and manipulate data. Also, enables to find meaning and appropriate information from large volumes of data. This makes it possible for us to use data for making key decisions in business, science, technology, and even politics.

4. Conclusion

As a result, we have briefly studied Data Science vs Artificial Intelligence vs Machine Learning vs Deep Learning. Also, we will learn clearly what every language is specified for.

More info please visit http://www.asiarfid.com/blog/comparison-between-data-science-vs-artificial-intelligence-vs-machine-learning-vs-deep-learning-en.html

Technology Helping Truckers & City Planners Reduce Traffic

Traffic and congestion are expensive and annoying problems for any city and its people. It seems to have been getting worse for a while, too. 

But city planners, government officials and pioneers in the private sector are now using technology to solve longstanding problems that affect everybody equally. The benefits to the economy could be even greater than the benefit to our collective mental health.

Cars Connected to Cars Connected to Cities

It sounds like the stuff of shiny futures, but the reality of autonomous cars that talk to each other — as well as with government data systems — is already here. It might also sound dystopian until you think of the many benefits.

Technology companies are testing driverless cars in some cities as we speak. And now, connected technology will help us turn them into the “advance guard” for things like traffic accidents and potholes. By exchanging data wirelessly, our cars will soon be able to alert one another about delay-producing events and make adjustments without intervention.

The benefits extend beyond daily commuters and will certainly make life easier for road crews and infrastructure workers — not to mention trucking companies and others who transport time-sensitive goods or for whom arrival time is of particularly vital importance.

City Planners Ensure There is No More Curb Kerfuffle

Those who live out in the country might not really “get” the singular frustration of curb use in big cities. Parallel parking is enough of a nightmare, but when you factor in things like loading zones, parking meters, fire hydrants, emergency lanes and more, the picture gets complicated. In our denser city scapes, it’s not uncommon for “curb interactions” to account for 30 percent or more of the traffic. Specifically, it’s cars looking for places to park or drop off passengers — and all of the trucks competing with them that need to unload products.

Now, with modern mapping technology and “mobile data” to share via the cloud with city planners and economic parties, the driverless cars of the future will know when the curbs are theirs for the taking and when they’re reserved for freight shuffling and truck parking. Autonomous cars drop their passengers off at the curb by day, trucks drop off cargo at night. A problem that used to cost Washington, D.C. alone $650 million every year might soon be a thing of the past.

Traffic Lights That Aren’t Horrible (or: No Traffic Lights at All)

The only thing more obnoxious about traffic lights is how the average driver behaves around traffic lights. Like that scene out of 1984’s “Starman,” a visiting alien wouldn’t last a second in an American intersection.

To be clear, traffic lights are a great invention — they just need a retrofit for the Twenty-First century. In a pilot program in Columbus, Ohio, government vehicles collaborated with public data-sharing programs to better understand traffic flow and greatly improve the “pacing” of their city’s traffic lights. We all know the frustration of lurching from light to light down major streets in our big cities. And it doesn’t get easier when larger delivery trucks enter the mix or when construction vehicles have to move about freely. But things get even cooler from here.

Autonomous cars are going to add their “collective intelligence” to the mix and potentially help us rid ourselves of traffic signals entirely. Those dumb black boxes are meant to signal to humans — so what about when humans aren’t driving?

Sooner than you probably think, driverless cars will be able to signal to one another and anticipate intersection crossings long in advance. Instead of halting cars to allow others to proceed, driverless cars will merely alter their speeds for moments at a time to avoid collisions and create a weird sort of ballet where cars simply come and go smoothly, meshing with other traffic the way a zipper’s teeth mesh together.

Driving the Future

Even now, the impact of higher technologies on fuel savings, economic performance and general operational efficiency is being hotly debated. Ironically, while driverless cars have the potential to reduce our collective energy use by 90 percent, many of those same experts warn that we might abuse our newfound freedom to sleep or party en route and in fact drive many more miles than we did before.

However, the technologies above could save us a lot of the trouble that comes from bad planning and impatience. We’ll understand the cultural influence better later on, and probably a brand-new branch of vehicular etiquette, too, but we have to build the future before we can live in it.

RFID for WIP Tracking Provides Visibility and Value

Being able to track and have complete visibility into your work in process (WIP) and all the parts moving through your supply chain is obviously valuable.

It’s even better when you can do it automatically and in real time.

Thankfully, there’s a proven and cost-effective way to achieve this with radio frequency identification (RFID).

Understanding RFID & Its Advantages

RFID relies on printed tags to identify and track assets as they move through your supply chain or processes.

Each tag contains a radio transmitter that operates like Wi-Fi, transmitting data wirelessly to a scanner, which reads the tag remotely.

Unlike barcode scanning, which requires line-of-sight access to the barcode and manual scanning, RFID automates data capture and tracking.

As a part or finished good moves through your processes and workstations, fixed RFID readers automatically detect and identify it.

These devices, such as Zebra’s FX9600 fixed RFID reader, are typically placed in strategic locations such as doorways and workstations. They read RFID tags automatically without requiring human labor.

As an alternative, operators and workers can use handheld RFID readers, such as Zebra’s MC9190-Z model. Handheld RFID readers read tags remotely, at long ranges, while also serving as mobile computers to run your business-critical software applications.

Teh Zebra FX9600 fixed RFID reader will read RFID automatically.

Handheld RFID readers like the Zebra MC9190 can read RFID remotely and on demand.

Importantly, RFID tags can also contain complex work instructions, bills of material, and tracking numbers. These allow operators to track and direct parts through your processes automatically, with easy access to all the part-specific information and instructions they need.

They can access it all on mobile computers, using a user-friendly app that also allows operators and managers to access real-time WIP tracking and reports.

A Real-World RFID for WIP Case Study

A perfect example of RFID’s value is its use by Troy Design & Manufacturing (TDM), a Ford Motor Company subsidiary. TDM now uses RFID to track, monitor and guide more than 150 daily vehicle conversions at its Chicago Modification Center (CMC).

TDM primarily specializes in prototype and short-run metal stamping, but also handles vehicle conversions. Ford manufactures police interceptors at a nearby plant. The interceptors are then sent to TDM for customization to meet the requirements of local law enforcement units including colors, lights, and other unique features.

In launching this new endeavor, the company realized a manual, paper-based tracking system wouldn’t be efficient enough to handle operations for 150 vehicles per day. Barcoding and fixed terminal entry simply wouldn’t provide the required level of automation.

To find a better alternative, TDM turned to the team at Lowry Solutions and worked together to develop an ideal solution.

A major component of the TDM plan was using Zebra RFID infrastructure technologies to achieve true, automated WIP tracking with real-time visibility into its entire vehicle conversions processes—from receipt to completion.

The system has delivered an array of benefits, including streamlining workflows, preventing downtime, and helping TDM’s operators stay more focused on their tasks with less need to worry about paper-based documentation or tracking duties.

VIN numbers, tracking numbers, work instructions, BOMs, and even time and date stamps are all captured and communicated automatically.

Since the Lowry WIP software interfaces with Ford’s corporate database, TDM also uses RFID to send Ford real-time reports of vehicle receipt, production progress and shipping updates.(From, Lowry)

More info at http://www.asiarfid.com/blog/rfid-for-wip-tracking-provides-visibility-and-value.html

How To Survive for Small IOT & M2M Startups

While it is good news that all kinds of predictions and current technology trends in the IoT world are steadfastly pointing towards everything except a declining IoT sector. The hype is such at this moment that Symantec’s Norton expresses blatantly:

And Norton is not the only one to describe such massive magnitudes of numbers for the devices connected by the IoT networks in the future, there is a wide range of other notable big names in the tech industry who are also throwing their own estimations on the future of IoT in the world. But in-between these huge numbers, we can safely say that the key names in the tech industry have much to gain, either in one way or another, but the point of discussion over here is about the sanctity of small IoT startups and businesses. According to the stats taken from the Angel List, there are approx. 4, 416 new IoT startups, 1, 727 investors, and a good 1, 779 jobs vacant, and all of this data is gathered within the States only.

Considering such growth, one may easily say that the IoT industry is fast-thriving, which is not a wrong statement to make, but one may never give a sure approx. of how many IoT startups among these are, or will, survive the period between the beginning and becoming of IoT as a mainstream industry. Therefore, there should have to be a succinct plan, or a policy, with which these new IoT & M2M startups should be aligned with to not only survive the initial set up period but to ultimately survive the long-term competitional era in-between other key players of the industry. To achieve this long-term success and an eventual “win-win” situation, every IoT startup owner might have his/her own custom planning in place, but over here in this brief narration, I would like to give some generic tips based on my own experience as a working Marketing Manager of a rising IoT/M2M business.

It is true that big ideas and dreams lead to bigger and well-known names. However, one thing must not control, or lead your ambitions in their primordial stages: “I will only use the topmost, biggest, well-known, and highly expensive IoT resources to grow my business much faster than the others.” A rising business, specifically of tech, has an abundance of cautious expenditures of its own.

Not applying a careful & moderate approach in the early stages, in a striving to deliver exceptional results, will most probably end up messing lots of processes and incurring extra unnecessary costs (a verified formula to destroy any startup). It is stated in no holy book of business planning that one should use expensive alternatives to succeed in his/her business, nor as a startup and neither as an established business, too. You can effectively seek out highly affordable, yet effective, IoT connectivity and M2M device management solutions for your IoT startups.

Consider what: It will always be good for your small IoT business to also use those very same IoT connectivity and management services providers who are also, just like yourself, have started and are working hard to rise to the top of the consumer chain list. A partnership such as this will give more featuresome services at a relatively reasonable cost; indeed, a verified formula for the success of any startup.

Confused? It is very easy to understand what is written above, let me explain. This is the age of the online world, and nothing can be more conducive for a startup than to remain cost-friendlier for some time in the early stages. Starting up as an online business is that solid first step towards a successful way to establish yourself as a reliable and well-known IoT business later. Set up a classy and niche-relevant IoT site, hire a team of experts in IoT online, get your first IoT project by effectively marketing your business to the targeted audience/businesses (for B2B startups), and finally kickstart your company towards many milestones to come in the future.

Trust me, starting from your IoT business online will keep the much-undesired pressure off from your wallet, and while you still had to invest for the essentials, your costs in an overall aspect will much lower as compared to having a brick-and-mortar office in the early stages. If in the case you somehow didn’t get the success you were looking after (I hope this may not happen), then it will be much easier for you to curtail all the things, and you may even go for another restart.

This, however, might not be too easier for a land-based office because the expenses involved can easily break up the backbone of someone who, unfortunately, becomes a victim of failure. Therefore, I would recommend for all IoT startup owners to first obtain benefit from the advantages offered by world wide web, and after establishing themselves online, they should go for a more elaborate version of their IoT business, which is to open a brick-and-mortar office of their own.