MTech IoT Projects 2026 — Advanced IEEE Research Topics for MTech CSE, ECE & EEE Students in Bangalore
MTech-level IoT research in 2026 is defined by four converging forces: intelligence at the edge (federated learning, TinyML, MEC), trustless infrastructure (blockchain, homomorphic encryption, quantum-safe cryptography), cyber-physical fidelity (digital twins, IIoT Industry 4.0, V2X) and resource-constrained sustainability (energy harvesting, LPWAN, perpetual sensor nodes). At ProjectsatBangalore, we have designed 25+ IEEE 2026 MTech IoT project topics that sit at these intersections — topics that hold a publishable research gap, are validated through simulation (MATLAB, NS-3, TensorFlow Federated) and hardware (Raspberry Pi, ESP32-S3, LoRaWAN gateway), and are documented to VTU / Anna University MTech thesis standards. Whether you need a federated learning MTech IoT project, a blockchain IoT security MTech thesis, a digital twin IIoT project, a 5G-enabled IoT dissertation, an energy harvesting MTech IoT project, a quantum-secure IoT thesis or a swarm intelligence IoT MTech project, every deliverable includes an IEEE Xplore base paper, algorithm/protocol design, complete simulation results, comparison tables, hardware prototype, dissertation-format report, PPT and viva Q&A support.
What Makes Our MTech IoT Projects Research-Grade
- Identified IEEE-published research gap — not a rehashed undergraduate project
- Mathematical model or algorithm/protocol innovation
- Dual validation: simulation (MATLAB / NS-3 / TFF) + hardware prototype
- Comparative evaluation against 3+ baseline methods
- Publication-ready results section with graphs, tables and statistical significance
- VTU / Anna University / JNTU MTech thesis chapter structure
- Scopus / SCI journal paper writing and submission guidance
- IEEE conference paper preparation (ICIOT, IoTDI, DCOSS-IoT)
⚡ Research Insight: Why Federated Learning + IoT is the #1 MTech Topic in 2026
Centralised cloud training of IoT data violates GDPR, produces communication bottlenecks and exposes raw sensor data. Federated learning (FL) trains models locally on IoT nodes, sharing only model gradients — but introduces Byzantine attacks, gradient poisoning and communication overhead. The research gap: efficient, attack-resilient, communication-compressed federated learning for heterogeneous IoT deployments. This is why FL-IoT dominates IEEE IoT Journal and IEEE TIFS submissions in 2026 — and why it makes the strongest MTech IoT thesis topic right now.
MTech IoT vs BE/BTech IoT — What is the Difference?
Understanding why MTech IoT projects require a completely different approach — novel contribution, algorithm design, simulation proof and publication readiness — compared to undergraduate implementation projects.
| Criterion | BE / BTech IoT Project | MTech IoT Research Project |
|---|---|---|
| IEEE Base Paper | Implements existing paper concept | Identifies gap in 3–5 IEEE papers, proposes extension |
| Novelty Requirement | None — replication acceptable | Mandatory — novel algorithm, protocol or architecture |
| Validation Method | Hardware demo / prototype | Simulation + hardware + statistical performance analysis |
| Simulation Tools | Arduino IDE, Proteus, Fritzing | MATLAB, NS-3, TFF, Cooja, Mininet-WiFi, OMNeT++ |
| Report Format | 6–8 chapters, 60–80 pages | 8–10 thesis chapters, 100–140 pages, APA/IEEE citing |
| Publication Outcome | Not expected | Scopus / SCI journal or IEEE conference paper |
| Complexity Level | Application layer integration | Protocol design, algorithmic innovation, security proofs |
| Duration | 3–6 weeks | 3–6 months (thesis) / 6–8 weeks (assisted) |
MTech IoT Research Stack — Simulation & Hardware Tools
Every MTech IoT project is validated using an appropriate combination of network simulation, ML framework, blockchain testnet, cloud-edge orchestration and physical hardware — ensuring credible, publication-quality results.
TensorFlow Federated
Flower FL Framework
NS-3 / Cooja
MATLAB / Simulink
Hyperledger Fabric
Ethereum / Solidity
AWS IoT Greengrass
Azure IoT Edge
Apache Kafka Streams
Python / PyTorch
LoRaWAN / LPWAN
Docker / K8s Edge
GNU Radio / SDR
Raspberry Pi 5 + AI HAT
FPGA Zynq / Artix
25+ IEEE MTech IoT Research Project Topics 2026
Every topic below is curated at MTech research level — with a clearly defined IEEE 2024–2026 research gap, novel contribution, recommended simulation tool, hardware validation platform and target publication venue. Available as MTech IoT projects with source code, full simulation files and thesis-format report for VTU, Anna University and JNTU students in Bangalore.
Federated Learning IoT Projects
Privacy-preserving distributed ML · Byzantine resilience · communication compression · non-IID data
4 Topics
| # | MTech IoT Research Project Title | Hardware / Platform | Simulation / Tools | Research Gap |
|---|---|---|---|---|
| 01 | Byzantine-Resilient Federated Learning for Intrusion Detection in Heterogeneous IoT Networks Using Clustered Gradient Aggregation | RPi 4B ×4 · ESP32-S3 · Switch | TensorFlow Federated · Flower · NS-3 · UNSW-NB15 dataset | Existing FL-IDS systems lack Byzantine fault tolerance under coordinated poisoning attacks in non-IID IoT topologies |
| 02 | Communication-Efficient Federated Learning with Gradient Sparsification and Adaptive Quantisation for LPWAN IoT Deployments | RPi Zero 2W ×6 · LoRaWAN GW | Flower FL · PyTorch · MATLAB · LoRaSim | Standard FedAvg consumes 40–60× more bandwidth than constrained LoRa nodes can sustain — no compression-aware FL protocol exists for LPWAN |
| 03 | Differential Privacy-Enhanced Federated Analytics for Smart Grid Advanced Metering Infrastructure with Formal Privacy Bounds | RPi 4B · Smart Meter Shield · Ethernet | TFF · PySyft · MATLAB · IEEE 118-bus AMI dataset | AMI federated analytics lacks formal ε-differential privacy guarantees — existing approaches sacrifice accuracy for privacy without mathematical proof |
| 04 | Hierarchical Federated Learning Architecture for Multi-Tier Industrial IoT: Edge Aggregation with Cloud Distillation | RPi 5 (edge) · ESP32-S3 nodes · AWS IoT | Flower FL · Docker · Kafka · TensorFlow · Mininet | Flat FL architectures cannot accommodate IIoT's three-tier device/edge/cloud hierarchy — stragglers and partial participation degrade model quality |
Blockchain IoT Security Projects
Lightweight consensus · smart contracts · decentralised device identity · supply-chain traceability
3 Topics
| # | MTech IoT Research Project Title | Hardware / Platform | Simulation / Tools | Research Gap |
|---|---|---|---|---|
| 05 | Lightweight Proof-of-Stake Blockchain for Constrained IoT Device Authentication with ECC-256 Identity Anchoring | RPi 4B · ESP32-S3 · Ethernet Hub | Hyperledger Fabric · MATLAB · Cooja · CryptoTool | Ethereum PoW is computationally prohibitive on μC-class IoT devices — no energy-audited PoS variant addresses IoT duty-cycle constraints |
| 06 | Smart Contract-Driven Autonomous Data Marketplace for IIoT Sensor Streams with SLA Enforcement | RPi 5 · Industrial Sensor Array · AWS IoT | Ethereum (Sepolia) · Solidity · Web3.py · Kafka · Grafana | IIoT data monetisation relies on centralised brokers — no trustless, self-executing SLA mechanism exists for real-time sensor stream trading |
| 07 | Blockchain-Anchored Digital Provenance for Pharmaceutical Cold-Chain IoT with Tamper-Evident Sensor Attestation | RPi 4B · DS18B20 · BME280 · NFC | Hyperledger Fabric · IPFS · Node-RED · Python · MATLAB | Cold-chain IoT logs are mutable in cloud databases — no blockchain-native sensor attestation protocol exists with regulatory traceability proof |
Digital Twin IoT Projects
Cyber-physical synchronisation · IIoT DT · predictive maintenance · simulation fidelity
3 Topics
| # | MTech IoT Research Project Title | Hardware / Platform | Simulation / Tools | Research Gap |
|---|---|---|---|---|
| 08 | AI-Driven Predictive Maintenance Digital Twin for Rotating Machinery Using Vibration, Thermal and Current Signature Analysis | RPi 4B · ADXL345 · IR Temp · ACS712 · Motor | MATLAB / Simulink · AWS IoT TwinMaker · TFLite · Grafana | Existing DT-PM systems use single-modal sensor fusion — no multi-modal fault isolation model achieves <3% false alarm rate on imbalanced IIoT datasets |
| 09 | Real-Time Digital Twin Synchronisation Protocol with Adaptive Sampling for Resource-Constrained Industrial IoT Networks | RPi 5 · ESP32-S3 ×6 · LoRaWAN GW | MATLAB · NS-3 · Azure IoT Edge · InfluxDB · Grafana | DT synchronisation assumes constant high-bandwidth links — no adaptive-rate protocol minimises cyber-physical divergence under lossy LPWAN conditions |
| 10 | Blockchain-Secured Digital Twin Audit Trail for Autonomous Manufacturing Cells with Tamper-Proof Provenance | RPi 4B · OPC-UA Server · Industrial PLC | Hyperledger Fabric · Node-RED · MATLAB · Mininet-WiFi | DT audit logs stored in centralised SCADA systems are mutable — no immutable DT-blockchain binding protocol addresses manufacturing compliance requirements |
5G / NR-IoT / Multi-Access Edge Computing
Network slicing · URLLC IoT · MEC task offloading · 5G-NR latency optimisation
3 Topics
| # | MTech IoT Research Project Title | Hardware / Platform | Simulation / Tools | Research Gap |
|---|---|---|---|---|
| 11 | Deep Reinforcement Learning-Based Dynamic Task Offloading in Multi-Access Edge Computing for Latency-Critical IoT Applications | RPi 5 (MEC server) · ESP32-S3 IoT nodes | Python · PyTorch DQN · NS-3 with MEC module · MATLAB | Static rule-based MEC offloading policies cannot adapt to dynamic IoT traffic — DRL approaches lack convergence guarantees under highly mobile node conditions |
| 12 | 5G Network Slicing Resource Allocation for Heterogeneous IoT Traffic: eMBB, URLLC and mMTC Co-Existence Optimisation | SDR USRP B205mini · RPi 5 · GNU Radio | NS-3 / 5G-LENA · MATLAB · Python · OMNeT++ | Current slicing algorithms treat eMBB/URLLC/mMTC isolation statically — no joint optimisation framework handles bursty mMTC alongside URLLC SLA guarantees |
| 13 | Energy-Aware Joint Computation and Communication Optimisation at MEC Nodes for Green IoT Using Lyapunov Optimisation | RPi 4B · Power Monitor · Wi-Fi 6 AP | MATLAB · CVXPY · NS-3 · Python · InfluxDB | MEC energy minimisation literature ignores correlated computation-communication energy — no Lyapunov-based online policy addresses queue-stability under non-stationary IoT arrivals |
Edge & Fog Computing IoT Projects
Fog-IoT architecture · real-time inference · containerised edge · anomaly detection at the edge
2 Topics
| # | MTech IoT Research Project Title | Hardware / Platform | Simulation / Tools | Research Gap |
|---|---|---|---|---|
| 14 | Fog-IoT Architecture with Containerised Microservice Inference for Real-Time Wildfire Detection Using Multi-Spectral Sensor Fusion | RPi 5 · AI HAT+ · Thermal Cam · Gas Array | Docker · K3s · TFLite · Kafka · Grafana · Python | Cloud-centric wildfire detection suffers 3–8 s latency — no containerised fog inference pipeline achieves sub-500ms detection with multi-modal sensor fusion |
| 15 | Cooperative Edge Caching Strategy for IoT Content Delivery Using Deep Q-Network with Proactive Content Prediction | RPi 4B ×3 · Wi-Fi 6 · NVMe Cache | Python · PyTorch DQN · Mininet-WiFi · NS-3 · Zipf model | Reactive edge caching in IoT networks ignores content popularity dynamics — no proactive DRL-caching model addresses non-stationary user request patterns |
Advanced IoT Security Projects
Quantum-safe cryptography · homomorphic encryption · zero-trust IoT · anomaly-based IDS
2 Topics
| # | MTech IoT Research Project Title | Hardware / Platform | Simulation / Tools | Research Gap |
|---|---|---|---|---|
| 16 | Post-Quantum CRYSTALS-Kyber Key Encapsulation for MQTT-Based IoT Communication with Energy Benchmarking on ARM Cortex-M | STM32F4 · ESP32-S3 · MQTT Broker · RPi 4B | Open Quantum Safe (OQS) lib · Python · Wireshark · MATLAB | RSA/ECC MQTT security is vulnerable to Shor's algorithm — no energy-benchmarked PQC integration exists for ARM Cortex-M class IoT devices |
| 17 | Homomorphic Encryption-Enabled Privacy-Preserving Analytics on Smart Building IoT Data Streams Without Decryption | RPi 5 · BACnet Gateway · CO2/Lux Sensors | Microsoft SEAL · TenSEAL · Python · Node-RED · InfluxDB | Smart building analytics require plaintext sensor data on cloud — no FHE pipeline processes BACnet IoT streams with acceptable latency for real-time control |
Wearable Health IoT Projects
TinyML on wearables · multi-parameter biosignal fusion · fall detection · remote patient monitoring
2 Topics
| # | MTech IoT Research Project Title | Hardware / Platform | Simulation / Tools | Research Gap |
|---|---|---|---|---|
| 18 | TinyML-Based Parkinson's Tremor Quantification on Ultra-Low-Power IMU Wearable Using On-Device LSTM Pruning and Quantisation | Arduino Nano 33 BLE · MPU-9250 · CR2032 | Edge Impulse · TFLite Micro · MATLAB · Python · PhysioNet | Cloud-offloaded tremor analysis fails in rural connectivity — no compressed on-device LSTM achieves clinically validated tremor scoring under 150 μA standby |
| 19 | Multi-Modal Biosignal Fusion IoT Platform for Continuous Atrial Fibrillation Screening with Federated Personalisation | RPi 4B · AD8232 ECG · MAX30102 · BME280 | TFF · TFLite · Python · MATLAB · PhysioNet AF dataset | Single-modal ECG AF detection suffers 12–18% false-positives — federated personalisation across heterogeneous wearable biosignal modalities is unexplored |
Precision Agriculture IoT Projects
LoRaWAN agri-IoT · satellite-sensor fusion · crop disease federated detection · autonomous irrigation
2 Topics
| # | MTech IoT Research Project Title | Hardware / Platform | Simulation / Tools | Research Gap |
|---|---|---|---|---|
| 20 | LoRaWAN-Based Precision Agriculture IoT Platform with Satellite NDVI Fusion and Explainable AI Irrigation Scheduling | RPi 4B · SX1276 LoRa · Soil/Humidity · GPS | Python · XGBoost + SHAP · LoRaSim · MATLAB · Sentinel-2 API | Ground-only IoT irrigation ignores large-scale canopy stress — no XAI-satellite-IoT fusion model provides farmer-interpretable irrigation schedules for smallholders |
| 21 | Cross-Silo Federated Learning for Rice Blast Disease Detection Across Multi-Regional IoT Camera Networks with Non-IID Mitigation | RPi 4B · Camera v3 · LoRaWAN GW · Solar | Flower FL · TFLite · Python · PlantVillage · MATLAB | Centralised disease detection violates farm data privacy across cooperatives — cross-silo FL with non-IID heterogeneity correction is unexplored in plant pathology IoT |
Energy Harvesting IoT Projects
Solar/piezo/RF harvesting · ultra-low-power design · perpetual WSN · duty-cycle optimisation
2 Topics
| # | MTech IoT Research Project Title | Hardware / Platform | Simulation / Tools | Research Gap |
|---|---|---|---|---|
| 22 | Hybrid Solar-Piezoelectric Energy Harvesting IoT Node for Perpetual Structural Health Monitoring of Bridges with Adaptive Duty-Cycling | ESP32-S3 ULP · Solar + Piezo PVDF · ADXL355 | MATLAB / Simulink MPPT · LTspice · Python · NS-3 | Single-source energy harvesting SHM nodes fail in low-light/vibration conditions — no adaptive duty-cycle algorithm jointly optimises two-source harvesting for perpetual operation |
| 23 | RF Energy Harvesting-Powered Backscatter IoT Sensor for Batteryless Indoor Asset Tracking with Deep-Sleep MAC Protocol | RF harvester PCB · STM32L0 · BLE backscatter | ADS-Momentum RF sim · MATLAB · Python · Cooja | RF-powered backscatter IoT systems waste harvested energy on idle listening — no deep-sleep MAC protocol co-optimises harvesting duty-cycle with backscatter transmission reliability |
Autonomous Vehicles & V2X IoT Projects
V2X DSRC/C-V2X · platoon control IoT · LiDAR-camera fusion · cooperative perception
2 Topics
| # | MTech IoT Research Project Title | Hardware / Platform | Simulation / Tools | Research Gap |
|---|---|---|---|---|
| 24 | Digital Twin-Assisted Autonomous Vehicle Platoon Control Over C-V2X IoT with Predictive Safety Gap Maintenance Using LSTM | RPi 4B · OBD-II · GPS NEO-M9N · 4G LTE | SUMO · NS-3 WAVE · MATLAB · TFLite LSTM · Python | V2X platoon control reacts to events after detection — no predictive DT-LSTM framework pre-empts dangerous gap closures from upstream IoT telemetry |
| 25 | Cooperative Perception IoT Framework for Autonomous Intersection Management Using Shared LiDAR Point-Cloud Compression | RPi 5 · OAK-D LiDAR · Wi-Fi 6 · V2I RSU | CARLA · ROS2 · Python · PointNet++ · NS-3 · PCL | Single-AV perception has blind spots at intersections — no lightweight point-cloud sharing protocol balances cooperative perception accuracy against V2I bandwidth constraints |
Swarm Intelligence & Multi-Agent IoT Projects
Ant colony optimisation IoT routing · drone swarm · MARL task allocation · bio-inspired protocols
2 Topics
| # | MTech IoT Research Project Title | Hardware / Platform | Simulation / Tools | Research Gap |
|---|---|---|---|---|
| 26 | Multi-Agent Reinforcement Learning for Adaptive Routing in Dynamic IoT Mesh Networks with Obstacle-Induced Topology Changes | RPi 4B ×5 · 802.11s Mesh · Raspberry Pi mesh | Python · RLlib (Ray) · Mininet-WiFi · NS-3 · MATLAB | Q-routing in IoT meshes converges slowly under rapid topology changes — MARL with inter-agent communication for obstacle-induced re-routing is an open problem |
| 27 | Bio-Inspired Ant Colony Optimisation Protocol for Energy-Efficient Data Aggregation in Large-Scale UAV-Assisted IoT Networks | RPi Zero 2W · NRF24L01+ · Pixhawk Drone | Python · MATLAB ACO · NS-3 UAV module · ROS2 · Gazebo | Hierarchical UAV-IoT data collection uses fixed clustering — ACO-based dynamic relay selection that jointly minimises UAV flight energy and sensor transmission cost is unexplored |
✅ All 27 MTech IoT research topics include: IEEE Xplore 2024–2026 base paper · Research gap definition & novelty statement · Algorithm / protocol design · Simulation validation (MATLAB / NS-3 / TFF) · Hardware prototype · Comparison results with 3+ baselines · VTU / Anna University thesis-format report (100–140 pages) · PPT · Viva & review Q&A · Scopus journal paper writing guidance.
Target Publication Venues for MTech IoT Research
Every MTech IoT project is designed with a specific Scopus / SCI publication pathway in mind. We provide complete journal paper writing, formatting, response-to-reviewer and resubmission support.
IEEE Internet of Things Journal
IF: 8.2 · Scopus Q1
Premier journal for federated learning IoT, digital twin and MEC MTech research — highest impact for MTech IoT publications
IEEE Trans. Industrial Informatics
IF: 11.7 · Scopus Q1
Best fit for IIoT Industry 4.0, digital twin IIoT, blockchain IIoT and AI-predictive maintenance MTech projects
IEEE Trans. Information Forensics & Security
IF: 6.3 · Scopus Q1
Ideal for MTech IoT cybersecurity, homomorphic encryption IoT, quantum-secure MQTT and FL-IDS projects
Future Generation Computer Systems
IF: 6.2 · Scopus Q1
Broad IoT + cloud/edge + blockchain scope — good acceptance rate for MTech IoT dissertation extensions
Sensors (MDPI)
IF: 3.4 · Scopus Q2
Fast peer-review open-access journal — excellent for wearable health IoT, energy harvesting IoT and agri-IoT MTech projects
IEEE ICIOT / IoTDI Conference
IEEE Indexed · Scopus
Flagship IoT conferences — ideal for presenting MTech IoT research results before journal submission
Frequently Asked Questions — MTech IoT Projects
Everything MTech students ask before selecting and beginning their IoT research projects in Bangalore.
A strong MTech IoT thesis topic in 2026 must satisfy four criteria simultaneously: (1) a clearly identified gap in at least three recent IEEE Xplore papers (2022–2026); (2) a novel algorithmic, architectural or protocol contribution that addresses that gap — not simply implementing an existing paper; (3) dual validation through network simulation (NS-3, MATLAB, TFF) AND a hardware prototype; and (4) results that compare your method against at least three baseline approaches using standard metrics (accuracy, latency, energy, throughput). Topics that sit at the intersection of two emerging domains — like federated learning + IoT security, digital twin + IIoT Industry 4.0, 5G-MEC + autonomous vehicles IoT or blockchain + healthcare IoT — generate the strongest novelty claims and attract IEEE IoT Journal reviewers' attention most readily in 2026.
The fundamental distinction is novelty vs implementation. A BE IoT project builds a working application from an existing design — a temperature monitoring system or a smart door lock. An MTech IoT project proposes a new method, proves it mathematically or through simulation, and demonstrates superiority over existing work. Concretely: you need a research gap statement, an original algorithm or protocol, a rigorous comparative performance evaluation, a 100–140 page thesis with APA/IEEE citations and — ideally — a Scopus-indexed conference or journal paper. The simulation phase alone (NS-3, MATLAB, TFF) typically takes 4–6 weeks. We accelerate this with pre-configured simulation environments, tested code bases and experienced research guides who have published in IEEE IoT Journal, IEEE TII and Sensors MDPI.
The choice of simulation tool depends on the research domain: NS-3 or OMNeT++ for network-level protocol research (5G-MEC, LoRaWAN, IoT routing); TensorFlow Federated or Flower for federated learning IoT; MATLAB/Simulink for signal processing, energy harvesting circuits and control systems; Hyperledger Fabric or Ethereum Truffle for blockchain IoT; SUMO + NS-3 WAVE for V2X and autonomous vehicle IoT; Cooja / Contiki for constrained embedded IoT nodes; and CARLA + ROS2 for autonomous drone and vehicle simulation. Most MTech IoT projects use at least two tools — simulation for theoretical validation and a physical testbed (Raspberry Pi, ESP32-S3, LoRaWAN gateway) for practical demonstration. We provide all these environments pre-configured in our Bangalore lab.
Yes. We offer complete Scopus / SCI journal paper writing assistance for MTech IoT research students — from selecting the right journal and formatting the manuscript to writing the literature review, algorithm description, results section and responding to reviewer comments. Our guided publication process has helped students publish in IEEE Internet of Things Journal, IEEE Transactions on Industrial Informatics, Future Generation Computer Systems (Elsevier), Sensors (MDPI), Computer Communications and multiple IEEE conference proceedings (ICIOT, IoTDI, DCOSS-IoT). Call or WhatsApp 9591912372 for a free consultation on your MTech IoT publication strategy.
We prepare MTech IoT thesis reports formatted exactly as per the guidelines of: VTU (Visvesvaraya Technological University), Anna University (Chennai), JNTU Hyderabad / Kakinada / Anantapur, Bangalore University, Mysore University, Mangalore University, Manipal Academy of Higher Education, Amrita Vishwa Vidyapeetham, PES University, RV College of Engineering, DSCE, MSRIT and all autonomous engineering colleges. Just share your university's thesis format guidelines when you contact us — we will customise the chapter structure, citation style (APA / IEEE / Vancouver) and formatting accordingly. Every MTech IoT project report includes all mandatory components: title page, certificate, acknowledgement, abstract, abbreviations, table of contents, 8–10 chapters, bibliography and appendix.
Assisted completion timelines (with our team doing simulation, hardware and writing): pure simulation-only MTech IoT projects (e.g., NS-3 protocol or TFF federated learning) take 3–4 weeks. Projects combining simulation + hardware prototype (e.g., federated IoT on RPi cluster, blockchain IoT with LoRa testbed) take 5–7 weeks. Full MTech IoT dissertation with publication support takes 8–14 weeks. If you have an upcoming internal review or viva deadline, WhatsApp us at 9591912372 immediately — we can discuss an accelerated timeline and deliverable schedule.
MTech IoT Research Lab — Bangalore
Our Bangalore research lab where MTech IoT projects are simulated, prototyped and validated — federated learning clusters, LoRaWAN testbeds, blockchain nodes, edge computing rigs and wearable health IoT platforms.
Federated Learning RPi Cluster
ESP32 / Edge IoT Testbed
Digital Twin / Cloud Dashboard
Edge AI / ML Inference Lab
MATLAB / NS-3 Simulation
Wearable Health IoT Platform
LoRaWAN Agri-IoT TestbedBlockchain IoT Security Node