Category: Mobile

How To Energize The Data Behind AI

Artificial intelligence (AI) is one of the biggest technology trends of the coming decade. In an increasingly digital world, propagating and collecting data are the default state of modern business and all internet activity. The problem for businesses is no longer the lack of data, but an excess of it. Despite the enormous data available to industrial companies, for most, their AI systems are not delivering the insights that they expected. The solution lies in filtering data so that the right data gets to AI systems. This “smart data” approach will allow AI systems to generate the kind of insights that we have expected. 

What is Smart Data?

AI is a key component of the fourth digital revolution. AI unearths insights from Big Data, insights that no human being could possibly unearth. The more data that AI has, the, the more variables it has, the longer its timescales and the greater its granularity, then, the greater the potential insights that it has.

AI can leverage years of data to discover the optimal parameters for industrial processes using controlling variables. These insights can then be used in these industrial systems to get them to work better than they did before. 

Despite the promise of AI, many industrial companies are yet to see the benefits of propagating and collecting so much information. According to McKinsey, although 75% of industrial companies have tried some kind of AI system, only 15% have enjoyed any meaningful, scalable impact from AI. McKinsey identifies the lack of operational insight into their usage of AI. This approach can be successful, but usually only within very specific parameters, and often with frequent retraining, lots of inputs, and sometimes, it leads to physical or unrealistic results. Therefore, these AI models cannot really be used in the real world or to get the kinds of meaningful change that its users expect. What you get are teams that become frustrated with the system and lose faith in AI.

Smart data is the solution. In order to leverage big data to get the kind of insights that it is expected to get, data has to have fewer variables governed by feature engineering based on first principles. This re-engineering of the data to produce smart data, added to more appropriate training can lead to superior returns of between 5% and 15%.

Smart data has been defined in a number of ways, but the essential features are that it refers to data that has been prepared and organized where it was collected in order for it to be ready and optimized for data analytics of higher quality, speed and insight. 

At a 2018 conference, Donna Ray, then executive director of the U.S. Department of Homeland Security’s Information Sharing and Services Office, said her “teams spend about 80% of their time just searching, ingesting, and getting data ready for analysis”. The smart data approach has helped federal agencies optimize their processes and speed up their operations and make them more intelligent. Wired described smart data as “Smart data means information that actually makes sense”. 

How Do You Generate Smart Data?

Get your Energize the Data! t-shirt out and let’s look at five steps to creating smart data. 

  1. Define the Data

The first step toward creating smart data is defining the process as you would a full coverage painting & flooring project. What this means is that processes must be broken down into clearly outlined steps for the company’s plant engineers and experts, with physical and chemical changes sketched out. The business’ critical instruments and sensors, limits, maintenance timeframes, measurement units, and their controllability must be identified. In physical systems, there are elements of determinism governed by clear equations. These equations must be noted as well as their variables. Teams must also understand the literature around these equations, in order to add to their own understanding.

  1. Enrich the Data

We’ve all heard the expression, “Bad data in, bad data out”, but the reality is, all data is in some sense bad data. Raw process data always has some deficiencies. So, your task is to improve the quality of the dataset, as opposed to increasing the amount of data available. Nonsteady-state information must be weeded out aggressively. 

  1. Reduce the Dimensionality

AI builds models by matching observables to features. In order to get a generalized model, the number of observations must be far in excess of the number of features. Inputs are often combined in order to generate new features. Factoring in the wealth of sensors that the typical plant has, the result is a vast trove of observations. What should be done, however, is to use inputs that describe the physical processes involved, funneled through deterministic equations, to reduce their dimensionality while also creating features that have intelligently combined sensor information. 

  1. Apply Machine learning

Industrial processes have deterministic and stochastic components. First-principle based features supply the deterministic components, and machine-learning the stochastic. Features should be evaluated to assess their importance and explanatory power. The most important, ideally, should be expert-engineered features. 

Plant improvements should be the focus of models, rather than achieving a maximum of predictive accuracy. High correlations are a feature of all process data. Correlations can therefore be meaningless. What is needed is to isolate causal elements and controllable variables.

  1. Implement and Validate Models

In order to actually enjoy the meaningful impact that is expected, models must be implemented. Results need to be continuously assessessed through the examination of key features to see that they match physical processes. Partial dependence plots must also be reviewed so we learn about causality and controllable elements must be confirmed. 

Operations teams must be consulted and made a critical member of the process to better understand what is implementable and what performance expectations make sense. Operators in control rooms need to get model results as they are generated, or teams must conduct on-off testing so that management can determine if it is worth investing capital in full-scale solutions. 

Conclusion

AI has enormous promise and certainly, with the wealth of data that is propagated and collected today, it is counterintuitive to suggest that limits or guard-rails need to be placed around that data. Yet, Big Data often fails to yield meaningful AI insights. Smart data can ensure that AI can deliver the meaningful impact that we expect.

How To Streamline Your App Development Workflow

As the shift to digital accelerates, the demand for new apps has surged. App developers face various challenges in meeting the market’s demands. There are funding constraints, a need to establish quality control systems, and other issues. The most immediate concern for app developers though, is how to work in an efficient and effective way. In this article, we will discuss how you can streamline your app development workflow in order to reduce development costs and speed up turn around times in your quest to build the next great app

  1. Start By Building a Code Library

Writing the actual code that will run your app is a vital part of your process, but it is a part of your process that takes up a big chunk of your time. For many app developers, they will be working from scratch, with very limited resources. Finding ways to write code efficiently is, then, very important. 

So what you need to do is to catalog any existing code in a library. This will improve your productivity by reducing the amount of time that developers will need to write and test new code. All that will need to be done is to retrieve code from the library and use it where needed in future app development projects. Consequently, your turnaround times will dramatically improve.

  1. Reduce your Data Storage Infrastructure

This sounds counterintuitive, because you often assume that the bigger your infrastructure, the better off you are. Yet having multiple databases only serves to increase the number of steps that your team has to go through to achieve their goals. 

Duplication is a likely result of having multiple databases. Often, teams find that they have databases that they do not need or even use, all the while increasing your security risks. Using a single database to store resources is much wiser from a workflow as well as a security aspect. Students in the best STEAM and STEM programs will be familiar with the importance of optimization. Having more than one database is not the best way to achieve optimization. 

  1. Use Layouts of Pre-Existing Apps

Using templates seems to be an admission of some kind of defeat for many developers. Yet, as the great scientist Isaac Newton noted, in order to see far, you should stand on the shoulders of giants. Take advantage of app templates in order to make a better product and work even faster. Using what came before you and worked well will help with your workflow in ways that are often underestimated.

Layouts will come with source code, which means that you will be able to skip a developmental stage by simply using that source code instead of writing it from scratch. There’s no need to consider things like UI/UX design, because someone else has already worked through those problems for you and come up with a solution you clearly like.

  1. Test! Test! Test!

Many apps fail because they are not rigorously tested. Developers kind of assume that their apps work well or that a few tests are enough to get an idea of the capabilities of the app. If you can test your app under the most extreme conditions, even if it seems unlikely that they will occur, you will be able to build a robust app that consumers will like. 
Running continuous tests is a great way to ensure that problems are dealt with as they arise and you receive almost immediate feedback at each stage of development.

What Is the Most Effective Work Email Product?

Too busy? Can’t handle your emails? Use the best work email product. Yet, to keep your vendors drawn in, you’ll need substantially more than that. In a perfect world, your emails will be something that they anticipate pursuing, so they’ll remember your business in any event, when they’re not yet prepared to purchase.

These emails’ objective is more for marking and narrating, as opposed to straightforwardly making a deal. Their motivation is to keep endorsers intrigued and drawn in with the brand, in any event, when they aren’t in a purchasing temperament.

Clients can likewise set updates for when to catch up on an email and timetable when they need their messages to send, if not right away. The application additionally holds messages quickly with the goal that clients can “undo send”.

Features of the best email work product:

Email Tracking

Email tracking implies checking opens and snaps of emails to catch up with drives, work candidates, and accomplices. It might then be alluded to as checking the measurements of your email marketing efforts to improve their quality and proficiency. 

You could utilize this tool for enrollment and third party referencing to spare time and realize when to develop with more emails if the beneficiary opened the email, however, never replied. They might have neglected to answer, or something might have upset their consideration.

Email Management

Email management is a particular field of interchange management for overseeing high volumes of inbound electronic mail received by associations. Today, email management is a fundamental segment of client assistance management. Client assistance call focuses on utilizing email reaction management specialists alongside phone uphold operators and ordinarily use programming answers for overseeing emails.

One of the key errands performed by email management frameworks is to assign reference numbers to every single approaching email. This cycle is known as tagging. All resulting emails identifying with one issue would then be able to be gathered under a similar reference. This permits clients to follow their correspondence in an additional time successful and profitable way.

Adds labels to each email for additional handling and may incorporate the capacity to associate with far-off information bases and recover explicit data about the email creator and his/her exchanges with the association.

Meeting Management

The target of these emails is more for checking and describing, instead of direct creation and arrangement. Their inspiration is to keep endorsers fascinated and attracted by the brand, regardless, when they aren’t in a buying demeanor.

  • You and the beneficiary can allude to the email later for insights regarding the meeting, for example, area, time, place, contact data or the purpose behind the meeting.
  • You and the beneficiary can quickly move the subtleties of the meeting to a schedule or sorting application with only a couple clicks.
  • An email can contain connections to RSVPs and headings.
  • An email permits you to control the precision of the time, spot and date of the meeting. At the point when you verbally arrange a gathering, there is an opportunity of blunder in note-taking.

Task Management

Task management is the way toward dealing with an undertaking through its life cycle. It includes arranging, testing, tracking, and detailing. Task management can enable either individual to accomplish objectives or gatherings of people work together and share information to achieve aggregate objectives.

Viable task management requires dealing with all parts of an undertaking, including its status, need, time, human and money related assets tasks, repeat, reliance, notices, etc. These can be lumped together extensively into the fundamental exercises of assignment management.

Now, you don’t have to work for yourself by using the best email product to get your tasks done. 

7 Ways Smartphones In Healthcare Are Becoming Vital

There’s a mobile revolution brewing from smartphones in healthcare.

According to the latest statistics, mobile health (mHealth) is expected to reach $21.71 billion by 2022. There are many factors that influence this market’s growth, but one of the most important is the adoption of smartphones and wearable devices into the healthcare industry.

Smartphones in healthcare will affect everyone, from patients to medical students, doctors and nurses, everyone uses a smartphone for health purposes. Here are a just a handful of ways smartphones are becoming indispensable to the healthcare industry.

1. Enable patient monitoring

Before smartphones, patients had to come to the hospital for physical check-ups or, if they had just underwent surgery, remain hospitalized for a couple of days, so doctors can closely monitor their recovery.
For doctors, that meant seeing more patients on a hard to maintain schedule. On the flip side, patients were spending tens of thousands of dollars on hospital stays.

Smartphones have made it possible for doctors to remotely monitor their patients, so that patients are able to recover in their home comfortable and without a hefty hospital bill. It also frees up doctors’ time to allow them to better serve more patients, lowering their workload and increasing profits.

What’s more, software as medical device (SaMD) enables wearables to collect health data and send it in real-time to physician’s mobile device via wireless technology such as Bluetooth. This makes caring for chronically ill patients a lot easier and less expensive.

Receiving real-time data about important changes in someone’s heart rate or glucose levels, for example, allows doctors to quickly tweak their treatment and avoid a trip to the emergency room.

2. Facilitate learning for medical students

Gone are the days when medical students carried textbooks heavy enough to give them a chronic back pain. Nowadays, all they need is a smartphone and their favorite medical apps.

According to an article published in The National Center for Biotechnology Information (NCBI), over 70 percent of medical school students reported using at least one medical app regularly.

This percentage will only increase in the coming years, with more medical apps created daily. Some grant students instantaneous access to evidence-based medicine or test their diagnosis and treatment skills. Others help them stay up-to-date with industry trends, guidelines and medical literature.

Small enough to fit in a lab-coat pocket, smartphones have become a medical student’s best study companion. Learning to become a doctor is easier and more convenient than ever before, thanks to these devices’ ability to store all their studying materials in one place.

3. Improve clinical trials’ efficiency

Clinical trials are a vital part of medical innovations. And smartphones are helping streamline the way they are conducted.

With the steady rise of bring-your-own-device (BYOD) in healthcare, smartphones are becoming more prevalent in mobile-enabled clinical trials. In trials with large numbers of participants, having patients use their own smartphone or tablet for data collection can drastically reduce costs.

It can also improve data quality and increase compliance. Patients are more likely to record important health information in real-time with devices that never leave their sides, versus jotting it down on paper hours later.

And if they happen to forget to document their symptoms or take their medication — which is often required in clinical trials? Researchers can send patients SMS reminders.

4. Make healthcare accessible and convenient via telehealth

Mobile devices are making healthcare available to more patients, regardless of their budget or their location. The use of mobile technology in healthcare is called telehealth and it allows patients to get 24/7 doctor support for urgent care, psychiatry and other conditions at a fixed cost.

What’s more, studies show telehealth to be just as effective as in-office visits when it comes to diagnosis and treatment planning for chronic conditions, even for difficult to treat conditions like psoriasis.

The growing popularity of telehealth services didn’t go unnoticed by the biggest pharmacy chains. Last year, for instance, CVS Health launched MinuteClinic Video Visits, a telehealth service that gives patients with minor illnesses and injuries around-the-clock access to health services. All from their phones.

5. Empowering patients to manage complex diseases

For patients with cancer and diabetes, managing their condition can be a full-time job.

This is where smartphones come in handy, helping them stay vigilant about their lifestyle.

Patients with complex diseases rely on their mobile devices to schedule doctor appointments or measure their vitals. They also use their phones to lower stress through meditation.

Most importantly, smartphones help patients stick to their treatment plans. A recent study showed that patients with tuberculosis (TB) were more likely to take their medication, if they received support via smartphones versus face-to-face appointments.

6. An accurate self-diagnosis tool

It’s incredible how many health conditions can be diagnosed with a smartphone alone. No need for expensive or painful tests.

There are iPhone apps that can determine if someone is having a heart attack with the same level of accuracy as a medical electrocardiogram.

Others are capable of diagnosing anemia by analyzing photos of a patient’s fingernail beds. And elders can self-diagnose osteoporosis using their smartphone’s motion picture sensor.

Many medical conditions have subtle symptoms and can go undiscovered for years.

Thanks to their mobile devices, patients can now seek professional help — and receive proper treatment — before their health deteriorates.

7. Prevent administrative and medical errors

Mobile devices enable doctors to have access to medical records and critical lab results, in real-time, while at a patient’s bedside. This leaves little room for error.

In fact, one study showed that mobile devices cut medication administration errors by 61 percent and preventable medical errors by 46 percent.

Smartphones are also improving response times for emergencies such as seizures or cardiac events. A growing number of hospitals have integrated smartphone platforms that send phone alerts to nurses and clinical teams whenever patients need immediate assistance.

To keep up with the demand, smartphone manufacturers have launched devices specifically designed for hospital environments. Phones like the Zebra TC51 and the Honeywell Dolphin can endure a drop on the floor and they can come into contact with body fluids and still work perfectly. What’s more, they have a minimum number of seams, so as to keep germ absorption to a minimum.

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It’s easy to see why iPhones are poised to become the new norm in healthcare. While there are lingering concerns surrounding the security of handling sensitive health data from mobile devices, smartphone manufacturers are working on developing features that ensure secure connectivity.  

In the end,  the pros of using mobile health (mHealth), and smartphones in particular, far outweigh the cons. This is why 40 percent of all hospital workers are expected to use a mobile device at work by 2020.