Cognitive cloud computing is a technology platform that combines machine learning, reasoning, natural language processing, speech, vision, and human-computer interaction in a way that mimics the functioning of a human brain. It facilitates better human decision making by allowing thorough data analysis.

For most of businesses, data collection and analysis are important to grow their market and have an insight into the customer experience. Cognitive cloud computing can help in an in-depth analysis of data for making informed and faster decisions. It also allows bringing together the data sets of different departments of an organization for facilitating holistic ideas for business growth.

Here are some applications of cognitive cloud computing in different business aspects:

• Chatbots: Chatbots understand the contextual meaning of communication to simulate a human conversation. The programs use a machine learning technique called natural language processing that helps in receiving human input, analyzing it, and providing logical answers. Cognitive computing helps the chatbots in implementing intelligence in communication like understanding user’s requirements based on past interactions, etc.
• Sentiment Analysis: It is a branch of science that deals with understanding the emotions conveyed in a communication. Unlike humans, it is difficult for machines to understand conversational aspects such as tone, intent, etc. In order to facilitate this, cognitive computing is used to feed the training data of human conversation to the machines and then analyze the accuracy. This helps businesses in understanding and analyzing user communications including social media interactions such as tweets, comments, reviews, complaints, etc. for delivering better customer service.
• Face Detection: Businesses are incorporating face detection for ensuring higher levels of system security. The security feature has numerous applications such as securing user access, security lockers, mobile phones, etc. The underlying process of face detection is an advanced image analysis. This is facilitated by a cognitive system that uses data like facial structure, contour, eye color, etc. to differentiate it from others. While traditional systems used 2D images, advanced cognitive computing techniques make use of 3D sensors that result in higher accuracy.
• Risk Assessment: Risk management and analysis is a major part of businesses. It requires a thorough analysis of market trends and historical data to predict uncertainties involved in an investment. However, big data analysis alone is not sufficient to do a thorough risk assessment. It also requires intuition, experience, gut feel, and behavior analytics. Thus, it becomes essential to make algorithms intelligent. This is made possible by cognitive computing as it combines behavioral data with market trends for generating meaningful insights that can be further analyzed by experienced analysts.
• Fraud Detection: Businesses need to detect frauds or anomalies in order to avoid situations that may cause financial loss or hamper brand image. This can be done with the help of programs that can analyze past data to understand perimeters to be used for judging a transaction. This is another business application of cognitive computing that involves techniques such as Logistic regression, decision tree, random forest, clustering, etc.

For more information on business applications and benefits of cognitive computing, call Centex Technologies at (972) 375 - 9654.

Cognitive cloud computing is a technology platform that combines machine learning, reasoning, natural language processing, speech, vision, and human-computer interaction in a way that mimics the functioning of a human brain. It facilitates better human decision making by allowing thorough data analysis.

For most of businesses, data collection and analysis are important to grow their market and have an insight into the customer experience. Cognitive cloud computing can help in an in-depth analysis of data for making informed and faster decisions. It also allows bringing together the data sets of different departments of an organization for facilitating holistic ideas for business growth.

Here are some applications of cognitive cloud computing in different business aspects:

• Chatbots: Chatbots understand the contextual meaning of communication to simulate a human conversation. The programs use a machine learning technique called natural language processing that helps in receiving human input, analyzing it, and providing logical answers. Cognitive computing helps the chatbots in implementing intelligence in communication like understanding user’s requirements based on past interactions, etc.
• Sentiment Analysis: It is a branch of science that deals with understanding the emotions conveyed in a communication. Unlike humans, it is difficult for machines to understand conversational aspects such as tone, intent, etc. In order to facilitate this, cognitive computing is used to feed the training data of human conversation to the machines and then analyze the accuracy. This helps businesses in understanding and analyzing user communications including social media interactions such as tweets, comments, reviews, complaints, etc. for delivering better customer service.
• Face Detection: Businesses are incorporating face detection for ensuring higher levels of system security. The security feature has numerous applications such as securing user access, security lockers, mobile phones, etc. The underlying process of face detection is an advanced image analysis. This is facilitated by a cognitive system that uses data like facial structure, contour, eye color, etc. to differentiate it from others. While traditional systems used 2D images, advanced cognitive computing techniques make use of 3D sensors that result in higher accuracy.
• Risk Assessment: Risk management and analysis is a major part of businesses. It requires a thorough analysis of market trends and historical data to predict uncertainties involved in an investment. However, big data analysis alone is not sufficient to do a thorough risk assessment. It also requires intuition, experience, gut feel, and behavior analytics. Thus, it becomes essential to make algorithms intelligent. This is made possible by cognitive computing as it combines behavioral data with market trends for generating meaningful insights that can be further analyzed by experienced analysts.
• Fraud Detection: Businesses need to detect frauds or anomalies in order to avoid situations that may cause financial loss or hamper brand image. This can be done with the help of programs that can analyze past data to understand perimeters to be used for judging a transaction. This is another business application of cognitive computing that involves techniques such as Logistic regression, decision tree, random forest, clustering, etc.

For more information on business applications and benefits of cognitive computing, call Centex Technologies at (972) 375 - 9654.

Hospitality industry is an umbrella term that includes lodging, food & drinks, event planning, theme parks, and transportation. The industry requires human-to-human interactions to maintain its operations. However, the spread of COVID-19 has caused a shift in the way humans interact with each other. In order to attract tourists and visitors, the hospitality industry needs to reassure the guests that their visit will be compatible with minimal social interaction and human contact.

This has given rise to the need for employing robots in the hospitality sector. Here are some ways in which robots can be used to suffice the needs of the hospitality industry:

• Hotel Management: It is a major part of the hospitality sector. Hotel management involves numerous tasks such as concierge, front desk, room service, cloaking, etc. These tasks require human interactions. However, robots can be used to efficiently complete these tasks while avoiding the need for human contact.
• Touch Less Check-in: Due to the growing need for no-touch technology, hotels are required to adopt new ways of facilitating check-in for the guests. Robotic technology can be used to incorporate convenient options such as fingerprints or iris & face detection instead of room keys.
• Bookings: Chatbots are commonly being used by many hotel chains and travel companies to assist their customers in completing simple tasks such as making online reservations. However, COVID-19 spread has given rise to the need for making use of robots for in-person bookings as well.
• Assistance: It is expected for the guests to be highly curious and vigilant about their travel and stay after COVID-19. Robots can be used as assistants at airports and hotels to assist visitors with their queries about safety, travel, ongoing events, etc. The robot assistants can also help the visitors by escorting them to their rooms.
• Serving Food: Taking order and serving food to guests at a restaurant or hotel requires close human interaction. Service robots can help the hospitality sector in combating this issue. These robots are capable of face and voice recognition to remember the order and deliver food to the concerned guest.
• Customer Satisfaction: In order to improve profits after COVID-19, hospitality managers are required to find ways for improving customer satisfaction for attracting a larger number of guests. Robots integrated with AI can be of immense help to the managers. They can be used to understand a guest’s behavior by tracking his history of bookings, type of services availed in the past, etc. The robots can use different software to recognize a guest and deliver customized services based on his behavioral history.
• Security: Security checking at hotels and airports is essential to ensure the safety of guests. Security robots equipped with features such as autonomous detection of concealed weapons can be used to make the guests feel more secure. These robots will enable the hospitality industry to conduct security checks without the need of individual checking by human security staff.

For more information on need of robots in hospitality service, call Centex Technologies at (972) 375 - 9654.

View Full Image

Data anonymization is the process of protecting private or individual sensitive information by either erasing or encrypting the personal identifiers that form the connection between an individual and stored data. This helps in retaining the data while keeping the source anonymous.

What Is the Need For Anonymization Of Patient Data?

• Data science including collection and analysis of patient data is of immense importance for improving healthcare. It forms the basis of healthcare research for improving drug discovery, predicting epidemics, designing advanced cures, etc.

However, the law requires healthcare researchers to keep the PHI (Personal Health Information) of people secure. So, the only way of using patient’s data for research is to get their consent beforehand. This places a limitation on the data sets as some patients may decline the consent. Data anonymization lifts certain restrictions as it removes the patient’s identifiers and renders the data anonymous. It provides healthcare researchers the ability to access extensive, coherent, and historic data that can be built upon without damaging patient trust.

• Second reason that emphasizes the importance of genuine anonymization of patient data is that patients may be reluctant to seek medical attention if they fear that their PHI may be shared with someone. Genuine anonymization helps the healthcare institutes in offering privacy assurance to their patients.
• An information leak or disclosure that an individual has tested positive for STIs such as HIV/AIDS can invite discrimination or social stigma. Anonymization of such data helps in reducing the risk of such disclosure and maintaining the privacy and confidentiality of patient data.
• Another reason for incorporating genuine anonymization of patient data in the healthcare industry is to keep the data secure from cyber criminals who may cause a data breach and negatively affect the patients.

What Data Anonymization Techniques Can Be Used?

Data Masking: Real data is hidden by altering values. For example, a mirror of a dataset may be created and the value characters may be replaced with symbols such as ‘*’ or ‘x’.

Pseudonymization: The private identifiers such as name, address, etc. are replaced with face identifiers or pseudonyms.

Generalization: Some of the identifier data is removed while retaining a measure of data accuracy. For example, removing house number from the patient’s address while retaining the road name.

Data Swapping: It is also known as shuffling or permutation. The dataset attribute values are rearranged so that they don’t correspond with original values.

Data Perturbation: The original data set is modified by adding noise to the data and rounding off the numbers such as age or house number of the patient.

Synthetic Data: An artificial data set is created instead of altering the original dataset based on patterns and statistical analysis.

For more information on the importance of genuine anonymization of patient data and methods of implementation in healthcare, call Centex Technologies at (972) 375 - 9654.

The advent of new technology has proven to be very helpful in combating diseases, especially pandemics such as COVID-19. If applied properly, technologies such as IoT, AI, and Big Data Analysis can be used to decelerate the propagation of the pandemic and avoid global health crisis in the future. Another technology that can be of immense help during a pandemic is ‘Connected Devices’.

Some applications of connected devices during a pandemic are:

• Monitoring Of Trends: Wearable devices, such as fitness bands, are widely being used for monitoring data such as activity, heart rate, sleeping patterns, etc. The data collected by these devices is continuously sensed and uploaded to the cloud. A thorough analysis of this data can help in the timely and accurate detection of trends that may be indicative of a population-level outbreak of any disease.
• Changing Patient Care Habits: A major concern during fighting a pandemic is to minimize contact with an infected carrier. Thus, isolation of patients is an important preventive action needed to control the spread of the pandemic. Connected devices such as thermometers, blood pressure monitors, glucometers, inhalers, etc. can help the patients in sending their health stats to the health care providers without the need of visiting the clinics. This reduces the risk of exposure. As these devices can be connected over a cellular network, patients can update their data from any location, regardless of the availability of WiFi coverage. Additionally, connected out-of-box cellular-based devices do not require the patients to have any knowledge of setting up a LAN/PAN connection.
• Quarantine Compliance: Smart cellular wristbands can be used to monitor the patients quarantined in their homes. These smart cellular IoT wristbands are small in size and have long battery life. The ability of these IoT wristbands to connect over a cellular network facilitates them to function independently from the patient’s smartphone. This helps the city management in ensuring that the patients are complying with quarantine rules.
• Improving The Reaction Time: Reaction time is a key factor in combating any pandemic. However, the timely reaction needs timely monitoring of symptoms and detection of contamination chains. Connected monitoring devices can help organizations, airports, malls, etc. in the effective and timely monitoring of people. These devices can also help in efficient monitoring of remote patients by healthcare professionals. This will help in the early detection of a pandemic resulting in reduced reaction time.

For more information on the key role of connected devices during a pandemic, call Centex Technologies at (972) 375 - 9654.

View Full Image

Outbreak of new diseases puts immense pressure on the healthcare system. Factors such as limited resources, a sudden rise in the number of patients, lack of established treatment, and vulnerability of medical staff add to the pressure on the healthcare system. In order to combat the outbreak of new diseases effectively, healthcare professionals require faster diagnosis, rapid response, effective use of human resources, and ensuring the safety of medical personnel.

In this scenario, medical AI is proving to be of immense use. Although the use of medical AI is not a new concept, the applications of medical AI have widened with the outbreak of new diseases and pandemics such as COVID-19.

• Diagnostics: Diagnosis of some diseases may require the doctors to compare a large number of CT Scans, check medical history, or other detailed reports. This is a time-consuming process and may result in delayed treatment causing negative effects, specifically in time sensitive cases. AI software helps in analyzing large amounts of patient data to assist doctors in diagnosing patients at a greater pace. This assists in lowering the treatment time.
• Risk Profiling: In the case of diseases that are contagious and spread easily, it becomes imperative to track the patients, travelers, tourists, etc. This helps in building a risk profile of the individuals. But manual profiling is time-consuming and prone to errors. On the other hand, AI-based risk profiling software has capabilities of historical geolocation and anomaly tracking of individuals in an efficient manner.
• Optimizing Drug Therapy: Effective and proper treatment of a new bacterial or viral infection requires a combination of different drugs. However, the process of searching for suitable drug molecules can be laborious, time consuming, and costly. It also requires numerous trials and can involve manual errors. AI-based systems help in optimizing the drug discovery process by searching the databases of complex drug molecules and matching the drug molecules with the target proteins. This reduces the research time and increases efficiency.
• Assistance For Medical Staff: AI-based apps can help the healthcare staff in gathering relevant information such as hospital-specific information, latest guidelines, operational directives, new treatments, protocols, drug dosage, and drug formulary. Well-trained AI systems can be used to analyze a patient’s reports and assign the case to a relevant specialist in the hospital.

For more information on increasing applications of medical AI, call Centex Technologies at (972) 375 - 9654.

Outbreak of new diseases puts immense pressure on the healthcare system. Factors such as limited resources, a sudden rise in the number of patients, lack of established treatment, and vulnerability of medical staff add to the pressure on the healthcare system. In order to combat the outbreak of new diseases effectively, healthcare professionals require faster diagnosis, rapid response, effective use of human resources, and ensuring the safety of medical personnel.

In this scenario, medical AI is proving to be of immense use. Although the use of medical AI is not a new concept, the applications of medical AI have widened with the outbreak of new diseases and pandemics such as COVID-19.

• Diagnostics: Diagnosis of some diseases may require the doctors to compare a large number of CT Scans, check medical history, or other detailed reports. This is a time-consuming process and may result in delayed treatment causing negative effects, specifically in time sensitive cases. AI software helps in analyzing large amounts of patient data to assist doctors in diagnosing patients at a greater pace. This assists in lowering the treatment time.
• Risk Profiling: In the case of diseases that are contagious and spread easily, it becomes imperative to track the patients, travelers, tourists, etc. This helps in building a risk profile of the individuals. But manual profiling is time-consuming and prone to errors. On the other hand, AI-based risk profiling software has capabilities of historical geolocation and anomaly tracking of individuals in an efficient manner.
• Optimizing Drug Therapy: Effective and proper treatment of a new bacterial or viral infection requires a combination of different drugs. However, the process of searching for suitable drug molecules can be laborious, time consuming, and costly. It also requires numerous trials and can involve manual errors. AI-based systems help in optimizing the drug discovery process by searching the databases of complex drug molecules and matching the drug molecules with the target proteins. This reduces the research time and increases efficiency.
• Assistance For Medical Staff: AI-based apps can help the healthcare staff in gathering relevant information such as hospital-specific information, latest guidelines, operational directives, new treatments, protocols, drug dosage, and drug formulary. Well-trained AI systems can be used to analyze a patient’s reports and assign the case to a relevant specialist in the hospital.

For more information on increasing applications of medical AI, call Centex Technologies at (972) 375 - 9654.

Every start-up faces two main challenges - testing the risk assumptions and collecting the maximum amount of validated information with the least efforts. Your first start-up app should offer solutions to these two challenges. There are no set layouts on how your first app version should look, however, there are two main guidelines every entrepreneur should be aware of:

• It Must Be An Answer To A Problem: The goal of first app version is to find out if your unique feature is valid enough to help you compete against the existing competitors in the market. Make it a point that app features should present the core of your solution in a compelling light. If the users are not convinced by the value of the core solution, they would not care to switch even if you provide add-on features.
• It May Not Be Automated: While automation may be a good feature to be included in an app, the first version of your start-up app need not be automated as far as it solves the user’s problems and allows you to test the risks. The purpose of your first app version is to help you de-risk the start-up and build your business on a stronger foundation.

Additionally, there are some key characteristics that you should keep in mind for building a successful start-up app:

• Simple To Use: The first and foremost characteristic that accounts for the popularity of an app is the simplicity to use. While it may be tempting to incorporate a lot of interesting ideas and third party widgets, it is important to keep in mind that the app will be used on mobile devices with limited screen dimensions. Thus, provide a simple user interface that is easier to use.
• Abolish Clicks: Attracting users to your app is important; making them stick to your app is equally necessary. Although, collecting user information is one of the underlying purposes of a app, do not overwhelm the users with multiple questions. Try to ask a minimum number of questions, banish unnecessary clicks, and avoid multiple taps in navigation.
• Multiple Device Compatibility: It is understandable that users are most likely to access the app on mobile devices so, make sure that your app is compatible with all the popular Operating Systems used across mobile devices such as iOS, Android, etc. Also, try to keep your app compatible with up to 2 versions prior to the latest update of these operating systems.
• User Feedback: Be sure to include the user feedback section in the app. It will provide valuable information about how your app works, ease of use, and improvements that users expect.
• Security: Security is crucial for the success of any app. Users will provide their details only if they are sure about the security of an app. So, pay attention to data security and other cyber security aspects of the app.
• Analytics: Analytics will help you to track user behavior while using your app and shed light on the feature that accounts for maximum user retention. This will allow you to develop popular features and work towards making your app succeed.

For more information on building your first start-up app, call Centex Technologies at (972) 375 - 9654.