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Menufacturing  manufacturing
Improve productivity, enhance safety standards and explore new growth avenues for your business. AR helps optimize manufacturing operations in many different ways, and drives revenue generation.
  • Acts as a training enabler leading to better, more accurate work
  • AR can aid safety training that helps workers understandsafety precautions
  • AR apps can be used to identify machine flaws quickly, thus reducing downtime
  • Day-to-day shop floor problems can be solved easily with real-time diagnosis.
Retails  retail
Drive more sales and engagement using AR to unify your online and offline retail channels and deliver an omnichannel experience to customers. Make a customer’s in-store experience more interactive or offer your customers an in-store experience, online.
  • An immersive retail experience that drives more engagement
  • Increase sales both online and offline
  • Beat your competition by doing something they might not be doinge
  • Reduce guesswork for customer, reduce product returns
Real Estate  Real Estate
AR is all set to revolutionize the real estate industry as it helps offer home buyers a clearer perspective of what their properties will look and feel like. This allows them to make better home buying decisions.
  • Save time spent in on-site visits
  • Offer potential customers clarity on the positives of a particular property
  • Quicker buying decisions help improve business profitability
  • Reach out to wide audience of buyers
Education  education
Deliver a hands-on learning experience to students through absorbing learning simulations. AR acts as valuable teaching aid, helping tutors make their point more effectively.
  • Students become an integral part of the learning environment
  • Facilitates intellectual development of students
  • Students are prompted to use their imagination
  • Drives successful learning outcomes
PR & ADVERTISING  PR & ADVERTISING
Take brand promotion to another level, ensuring target customers are more in sync with your products and services. We use AR to ensure your efforts to promote your products become more experiential.
  • Improve impact of promotional messaging
  • Increased ROI from branding efforts
  • Better customer connect
  • Adds a touch of fun and excitement to your advertising endeavors
Gaming  GAMING
With AR, game play becomes more realistic and gamers experience more advanced visuals that are more impactful and engaging. We integrate dramatic art, 3D sounds and more to deliver a captivating experience to gamers on their devices.
  • More downloads, means better profitability
  • Higher ROI from games development
  • More compelling games, recurring in- app revenue
  • Enhance target audience connect
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Enterprise Mobility Trends

Latest Enterprise Mobility Trends To Follow In 2019

Enterprise Mobility Solution is a budding trend that is rapidly grasped by the global market to enhance the productivity irrespective of the workspace. The organizations who consider mobile application as a top priority are experiencing more numbers of work hours yearly on an average. With the latest trends in digital transformation, integrated innovations and cloud computation, the enterprise mobility is going to play a significant role in 2019.

In the recent years, the focus has been shifted from data models to service models. Mobile apps and portable devices are becoming the cloud for scrambling services. Here you can explore the top enterprise mobility trends of 2019.
  • Function-friendly apps:
    Enterprises are looking towards more specific feature app for both of their employees and customers. Demands for enterprise mobile app has been increasing, which aims to make a particular function of the organization easy instead of pasting the entire features of the desktop site.
  • Virtual personal assistants:
    The trend to develop ‘smart’ application is on top today. And admiring special assistant services offered by Siri, Cortana, and Google Now, more and more enterprises are adopting it widely. The industries are embracing virtual assistant to save time, reduce error and improve the efficiency of the employees.
  • Moving to the cloud:
    Cloud computing has travelled a long journey and now it is established as mature, affordable and reliable service and source of data. The enterprise mobility is quite impossible without adapting to the cloud. All the critical data is saved, shared and operated in the cloud, which makes Enterprise mobility development more flexible and accessible.
  • Bring Your Own Device:
    A novice culture, which is setting the trends for future and laying a platform to explore enterprise mobility. BYOD is widely entertained by the corporate world and more than a trend, it established as norms in many companies. With mobile device management solution, BYOD concept is improving the fluidity of work carried out on devices.
Security Trend In Mobility Solution 2019

With open and mobile data sources and application, enterprise mobility solutions become more vulnerable to the security breach. Effective threat management, hybrid solution for hosting critical apps and control over the devices and cloud would come as a responsibility with the latest trends. Moving towards 2019, we will see security measures like biometric authentication to access data, device or services, tracking device information and location to set the security threshold of the workflows and device protection against malware and viruses. Especially, Android and cross-platform enterprise application would get more IT focus.

For tapping into the latest trend, you need sound professionals as your development partners and Technostacks is the optimum choice in this context. Our experience and expertise both allow you to leverage the latest tools and technology in the cost-effective manner to get highly intuitive Enterprise Mobility Solutions.

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Machine learning in agriculture

Role of Machine Learning in Modern Age Agriculture

Machine learning is a trending technology nowadays and it can be used in modern agriculture industry. The uses of ML in agriculture helps to create more healthy seeds.

The principle that Arthur Samuel used earlier in machine learning experiments are used in today’s modern agriculture. Artificial machine learning in agriculture is one of the fastest growing areas. Artificial techniques are being used in the agricultural sector to increase the accuracy and to find solutions to the problems.

Agriculture plays a very pivotal role in the global economy of the country. Due to the increase in population, there is constant pressure on the agricultural system to improve the productivity of the crops and to grow more crops.

A) Machine Learning Methods

In machine learning agriculture, the methods are derived from the learning process. These methodologies need to learn through experiences to perform a particular task. The ML consists of data that are based on a set of examples. An individual example is defined as a set of attributes. These sets of characteristics are known as variables or features. A feature can be represented as binary or numeric or ordinal. The performance of the machine learning is being calculated from the performance metric.

The performance of the ML model improves as it gains experience over time. To determine the performance of ML models and the machine learning algorithms agricultures various mathematical and statistical models are used. Once the learning process is completed, then the model can then be used to make an assumption, to classify and to test data. This is achieved after gaining the experience of the training process.

agriculture with Machine Learning

Image Source:- mindbowser.com

Machine Learning Functions

It can be divided into two categories, namely supervised and unsupervised learning.

  • Supervised Learning
  • In this machine learning agriculture method, the input data is represented with examples to the corresponding outputs. The primary goal of this function is to create a rule that will map the inputs to the corresponding outputs. In some cases, the inputs might not be available that may lead to missing output. The trained model is then used in supervised learning to predict the disappeared production and then the data is being tested.

  • Unsupervised Learning
  • In this machine learning agriculture technique, there is no difference between the trained models and the test sets, while unlabeled data is being used. The goal of this method is to find the hidden patterns.

B) The Machine Learning (ML) Evolution in Different Areas

Machine learning is evolving along with big data technologies and other fast computing devices. They are growing to create new opportunities to understand the various data processes related to the environmental functions of agriculture. Machine learning can be defined as the scientific method that will allow machines the ability to learn without programming the devices. Machine learning is used in various scientific areas such as Bioinformatics, Biochemistry, Medicines, Meteorology, Economic Sciences, Robotics, Food Security and Climatology.

C) Uses of Machine Learning (ML) in Agriculture

Artificial Intelligence is being used in various sectors from home to office and now in the agriculture sectors. Machine learning in agriculture used to improve the productivity and quality of the crops in the agriculture sector.

  • Retailers
  • The seed retailers use this agriculture technology to churn the data to create better crops. While the pest control companies are using them to identify the various bacteria’s, bugs and vermins.

  • AI is used to boost the yield of crops
  • The AI technologies are used to determine which corn and which conditions will produce the best yield. It will also determine which weather condition will give the highest return.

  • AI helps to identify bug hunters
  • One of the companies named Rentokil is using AI to kill all the bugs and vermin. Other companies are making use of Android app which is developed by Accenture to find bugs. The app takes the pictures of the bug and runs the app called as PestID. When a bug is found app will provide an immediate solution which helps the technician to take further actions. It will also recommend the chemical to be used to kill the bugs.

D) Most Popular Applications of Machine Learning (ML) in Agriculture

Let us look at the various applications of machine learning in agriculture.

  • Agriculture Robot
  • Most of the companies are now programming and designing robots to handle the essential task related to agriculture. This includes harvesting crops and works faster than then human laborers. This is the best example of machine learning in agriculture.

    machine learning farming robot

    Image Source:- yourvippartner.com

  • Monitor crop and soil
  • Companies are now making use of technologies and deep learning algorithms. The data are then collected using the drones and other software to monitor the crops and also the soil. They also use the software to control the fertility of the soil.

    By making use of new technologies in agriculture, farmers can find effective ways to save their crop and also protect them from weeds. Companies are developing robots and automation tools to achieve them. Agricultural spray machines are designed, See and Spray robot that is being developed by Blue River Technology will monitor and spray accurate weeds on the plant like cotton. The precise amount of spraying can help to reduce herbicide expenditures.

    Plant breeders are looking out for a particular trait on a regular basis. They look up for the qualities that will help the crops to use more water efficiently, use the nutrients and also adapt to the climate changes or any diseases. If the plant needs to give the desired result the scientist need to find the right gene. Find the correct sequence of the gene is difficult.

E) Machine Learning (ML) Models Used in the Agriculture Industry

  • The agricultural farmers are now taking advantage of the machine learning models and their innovations. Using AI and machine learning is good for the food tech segments.
  • The Farmers Business Network that is being created for the farmers a social network will make use of the ML and the analytic tools to drive the results of data on pricing.
  • Robots are now managing the crops and also monitoring them.
  • Sensors are helping to collect the data related to crops.
  • According to research if AI and ML are being used in agriculture, then the agriculture sector will grow in the coming years.

F) Rising Opportunities of Machine Learning (ML) in Digital Agriculture

There is a rise in digital agriculture, which uses a secured approach to give maximum agricultural productivity by reducing the impact on the environment. The data that is generated in modern agriculture is based on various sensors that will help in better understanding of an environment like the crop, soil and the weather conditions and also about the agricultural machines. These data will help us to take quick and fast result-oriented decisions. To yield more, we need to apply machine learning to agriculture data.

G) Real-life ML Example

A Mexico based Startup Company Descartes Labs are combining the satellite images, ML, Cloud computing and sensors to a better understanding of industries related to agriculture and energy. The company uses new technology in agriculture to discover where crops are situated and how good and healthy the crops are.

The machine learning tools which were reserved for some institutions are now accessible to all small and capable members. A small startup is making use if AI and machine learning to bring change in the modern agriculture sector. They are trying to reshape the contemporary agriculture sector by making use of innovative technologies.

Moving Forward

If you are looking for progressive Machine Learning solutions, you have come to the precise place. We at Technostacks have the right capabilities to build clear-cut machine learning solutions that are supported by our in-depth acquaintance of industry applications, business-based services and the linked assortment of our diverse range of technologies.

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CEBIT ASEAN thailand 2018

Technostacks: Meet us at CEBIT ASEAN Thailand – 18th to 20th October, 2018

CEBIT Thailand is ASEAN’s business platform, festival for innovation and digitization. The event will be held from October 18 to 20 at IMPACT Exhibition and Convention Centre in Muang Thong Thani. It is hosted by the Ministry of Digital Economy & Society and the Minister of Science and Technology (TBC). The event will pull technology professionals in Southeast Asia, from varied industries demonstrating the entire breadth of the technology sector.

CEBIT ASEAN will feature an exhibition and a conference programme. Admission to the CEBIT ASEAN THAILAND is constrained to trade professionals only. And the dress code for entry is firmly business-wear.

Business Networking Opportunities at CEBIT ASEAN Thailand

There has never been a more imperative time to do business in the swiftly evolving world of technology and this event offers boundless possibilities for businesses wishing to be at the front of innovation, technology, infrastructure and culture. It will cover Cloud Technology, IT Security, Big Data, IOT, Software and Hardware Solutions; to Emerging Technologies.

And will attract technology professionals and business leaders from assorted industries including financial services, healthcare and government, manufacturing and media, indicative of the complete breadth of the technology sector.

Technostacks will be participating at CEBIT ASEAN Thailand

Technostacks, who specializes in mobile app development, software development, web and e-commerce solutions, digital marketing and cloud based services will exhibit at CEBIT ASEAN Thailand 2018 at Hall 7-8, IMPACT Exhibition & Convention Centre, Bangkok, Thailand.

The company has its business presence in the USA, Germany, UK and India. It works on advanced technologies covering Angular JS & Node JS, Liferay Development, .Net Development, IOT (Internet of Things), AR, VR, ML, AI, and Salesforce. The company is highly committed to supporting digital industry development and progression. It innovates solutions in Augmented Reality, Embedded System, Wearables, Beacons (Context Awareness), Blueetooth low energy (BLE) Artificial Intelligence as well as in Machine Learning.

Let’s Meet Technostacks for your requirements

The event will offer an assortment of networking opportunities through personal meetings. Technostacks will be a focus for technology professionals and business leaders from varied industries including finance, medical, manufacturing, media and other technology domains. Businesses or individuals looking for any category of IT solutions are welcome to connect with us. So, let’s fix up a meeting for your IT requirements at below contact details.

Contact Details:

Website: https://technostacks.com/
Email: info@technostacks.com
+919909012616

If your organization is in the technology business and/or digitization you should reserve your booth today itself!

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