With over 60% world population expected to live in cities by 2050, cities are digitally transforming to improve the quality of life for its residents. Municipalities and local government bodies are using Internet of Things (IoT) systems and devices to turn their physical workspaces into digital and virtual entities. These digital workplaces can then be controlled and monitored from an IoT integrated platform. Data from these connected devices can be used to create more optimized and predictive operations.
NAlliancetech’ next-generation integrated solutions for Smart Cities use sensors, connected devices, and embedded systems with wired and wireless (Bluetooth, Wi-Fi and 4G/LTE) technologies to provide a more collaborative, flexible, and connected ecosystem. The integrated smart city solutions, such as smart parking, smart ticketing, smart toll collection, smart charging, smart home, etc., enable you to remotely operate devices and access services anytime anywhere. NAlliancetech’ smart city solutions enable clients to improve quality of lives and their productivity by manifolds. The company enables you to capitalize on IoT solutions as well as achieve an edge by gradually migrating to the Internet of Everything (IoE) paradigm for smart cities.
SMART CITIES OFFERINGS
Get access to an easy-to-use, interoperable fare medium that is cost-effective and secure. NAlliancetech has expertise spanning various ticketing systems, including magnetic paper tickets, contactless smart tokens, QR code tickets, and NFC tickets. These smart ticketing systems use closed-loop smartcards as well as open-loop EMV bank cards. These systems reduce fraudulent ticketing practices and operational costs. The smart ticketing solutions enable citizens to seamlessly access multi-modal transit.
Smart Toll Collection
Collect tolls electronically through an integrated platform consisting of technologies such as RFID tags, RFID readers, geo-location, automatic number plate recognition, and mobile apps. The combination of RFID tag-based vehicle identification with automatic number plate recognition allows the toll operator to introduce open road smart toll collection (decongestion charging) and helps transport authorities reduce congestion at the toll plazas and on the roads.
Use IoT technology in smart parking systems to tell commuters the number of vacant spots that may be available in a parking lot. Use intelligent sensors, connected devices, GPS, smart phones, and other integrated embedded technologies in smart parking to provide commuters with real-time parking data, such as space availability, local parking laws, parking times, etc. Use real-time data to apply dynamic pricing based on space availability and maximize revenues and profits.
Smart charging systems
Smart charging systems are designed to provide convenience and ease of use to commuters looking for easy payment options in return for using mobility services. With the help of sensors, front-end devices, device terminal management, central systems, and backend systems, NAlliancetech’ smart charging systems ensure accurate pricing and prevent fraudulent cashing. The system ensures safe and secure payments while charging a smart vehicle or a smart device or engaging a mobility service.
Smart home Kit/ Smart Device Solutions
Get easy and secure access, and remotely manage all devices and accessories connected with smart home automation frameworks and platforms. NAlliancetech has proven expertise in developing iOS mobile apps that are fully compatible with the Apple HomeKit and other home automation frameworks enabling multiple accessories to work in tandem. The apps strictly comply with the respective API guidelines.
Artificial Intelligence solutions enable the automation of medium to complex processes and take Robotic Process Automation to the next level. It powers predictive maintenance of heavy machines thus reducing operational costs. AI enables pattern identification with vast data volumes thus augmenting human intelligence and decision making. It improves the analytics domain to the nth extent. While Natural Language Programing (NLP) algorithms read and augmedata nt to produce analytical reports, Natural Language Generation (NLG) algorithms write sentences.
AI joins the dots from disparate data sources and discovers interesting patterns that are less visible to the human eye and intellect. Consistent variations, clustering of data points, dependencies, etc., bring forth interesting stories from the stagnant data resources. Using data, AI-enabled information mining generates hypotheses, verifies them, and deduces information. Information Mining forms the basis of Predictive Analytics and Machine Learning.
AI-powered Data Mining enables users to perform different levels of tasks –
Anomaly detection, where unusual patterns or outliers are thrown up, which may be errors or require deeper investigation
Associations, where the relationship between two or more variables are brought forth, and is frequently used in forensic investigations
Clustering, where data points that are similar in more than one ways are discovered
Classification, where known structures are generalized in order to apply to new data points; for example: Records or File Classification
Regression, where a function is found, which models the data and estimates the relationship between different data points
Summarization, where a concise summary is generated based on weighted keywords. It is popularly used for generating audit reports and executive summaries.
AI simplifies Document Management to a great extent. It enables automatic file classification or categorization as well as summarization. The files may include spreadsheets, documents, emails, PDFs, video files, audio files, social media, news, and other data types.
AI algorithms generate intelligence from high data volumes by correlating disparate data points. This data may comprise structured, unstructured, and multi-structured data.
A recent feature is AI-enabled Topic Modelling. It allows screening of huge data sets, such as reviews, emails, social media snippets, etc., and segregating them as per the predominant sentiment.
AI algorithms use weighted keywords and correlate them to generate concise summaries of lengthy documents, news articles, research papers, agreements, books, tweets, etc.
It uses two methods – Extractive and Abstractive. Extractive Summarization extracts several portions of the text and stacks them to create a summary. Abstractive Summarization uses NLP algorithms and generates a new summary.
AI-powered document summarization is used in audits, research study scenarios, social media listening, government services, etc.
How AI Is Transforming The Way Enterprises Use RPA