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NETVENTUS

 

DATACENTERIC   BUILDING   BLOCKS

 


IOT  AI   SOLUTIONS


NETVENTUS one-stop services spans entire IoT spectrum including IoT sensor and devices, IoTgateway, cloud computing, AI and ML tools, system integration, analytics.

In today's digital age there is a tremendous amount of IoT data and need for secure, self-managed platforms . Be it with retail, healthcare, automotive, industrial and numerous other cases

iot sensors ai ml

IoT

Sensors and Actuators

Sensors are the "Things” of the system. Their main purpose is to collect data from its surrounding (sensors) or take action (actuators). Examples of sensors are gas, temp, moisture, motion etc

Device

The IoT devices (IoT boards) typically have a firmware, OS/RTOS to process data, perform messaging and communication, manage data storage and manage actuator operations. OS pool includes Embedded Linux, TinyOS, Snappy Ubuntu Core, Contiki, FreeRTOS, Mantis, ARM's mbedOS, Android Things, RIOT OS, Windows 10, Nucleus RTOS, WindRiver VxWorks, BrilloOS Generic devices based on Arduino, Raspberry Pi, Beagle Bone, CubieBoard, Pinnocio, Banana Pi as well as custom systems are available.System features include stackable baseboards, Microcontroller / Microprocessor on-board memory, GPIO and supported communication protocols include USB, I2C, SPI, TWI, Ethernet

Gateway

Gateway collects and extracts upstream bound sensor data as per the device protocol, converts/formats to its upstream network protocol and sends it to cloud server. Similar process happens for downstream bound data.

Procotols

Physical/link layer - 6LoWPAN, Bluetooth/LE, 802.15.4, LTE, GPRS, NFC, Zigbee, 802.11, LoRaWAN

Network layer - IPv4, IPv6

Transport layer - TCP, UDP, DTLS, TLS

Application layer - DDS, MQTT, REST, CoAP, XMPP, AMQP, XMPP-IoT, MQTT-SN

Cloud Server

The cloud server is the edge of the IoT system and provides a platform for building applications. Functional layers include data aggregation ,data mining, analytics, network monitoring, communicate with other private and public cloud services

IoT Applications

The processing, mining and analysis of the data at for the end use . An IoT application typically process data from sensors and alswo may send commands to IoT Device to perform action From tracking the flow of people and traffic density to monitoring fluctuations in office temperature, crop moisture levels, traffic or patients’ vital signs, we manage over a thousand data points

Industrial IoT 4.0 integrates with legacy industrial protocols such as MODBUS, BACnet, and SNMP and provide remote SCADA systems monitoring , diagnostics, remediation, production planning, inventory management

IoT ecosystem is secured by robust identity management, encryption, firewall and antivirus capabilities and By delivering firmware updates over-the-air (OTA) for important security and feature patches

Retail solutions include Footfall and dwell-time sensors offer market insights that elevate the customer experience, enhance convenience levels, and influence online and in-store behaviors


AI/ML

In todays digital age, security teams face increased complexity as rogue elements use powerful automated tools , threatening security and network performance. Artificial intelligence (AI), Machine Learning (ML) can help by self-learning, automating and speeding up threat detection and remediation

AI: An umbrella term which implies intelligence demonstrated by machines

ML: uses data to make predictions or perform a task, learning to make decisions on its own

Deep Learning: An ML technique in which data is filtered through self-adjusting networks


Supervised Learning- with correctly labeled data, system analyzes and logic to unlabeled data

Unsupervised Learning - with unknown solution sets, system analyzes for patterns and then labels data

Reinforcement Learning - Optimizing the system’s logic by testing it with unlabeled data and offering grades (rewards) for the results. In other words, system takes suitable action to maximize reward in a particular situation

Some of the algorithms and tools used include Bayes, Linear and Logistic Regression, KNN, Decision Tree, Scikit, Numpy, Keras, Tensorflow, Sagemaker,Mxnet, Torch

There are numerous new and legacy components involved for building the right and flexible IoT and AI solutions and most companies cannot afford to hire and train staff for specific domain . With our expertise, you will be able to get complete IoT and AI solutions solutions while preventing your IT budget to baloon. We offer best-in-class platform components with capex optimized solutions for outstanding capex & opex savings, flexibility, life of products. Our solutions also leverage well-proven and widely deployed Vendor-specific and Open technologies, with separate software and hardware components for maximum flexibility. Sometimes simple and well proven solution could be all you need

NETVENTUS open, modular solutions built on datacenteric building blocks encompasses industry verticals including Manufacturing, Retail, Automotive, Healthcare, Warehouse, Hospitality, Construction, Education, BFSI, Public Transport, Safe and Smart city


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