Cloud computing and Internet of Things (IoT) Projects that are done by us are shared below these are fast emerging domains that encompass a wide range of research areas to develop projects. Related to cloud computing and IoT, we suggest some interesting projects. To handle, examine, and visualize data that are gathered from IoT devices, these projects utilize the cloud environments’ capability:
- Smart Home Automation System
- Explanation: To enable users to regulate and track home appliances in a remote way, a smart home framework should be created with cloud services.
- Mechanisms: Node-RED, MQTT, Raspberry Pi/Arduino, Google Cloud IoT, and AWS IoT Core.
- Major Characteristics: Mobile app incorporation, automated practices, actual-time tracking, and device control (security cameras, thermostat, and lights).
- IoT-Based Health Monitoring System
- Explanation: In order to gather data from wearable devices, a health monitoring framework must be developed. For analysis and warnings, this framework should transmit the gathered data to the cloud.
- Mechanisms: Python, MQTT, sensors (blood pressure, heart rate), Google Cloud Healthcare API, and AWS IoT Core.
- Major Characteristics: Actual-time gathering of health data, data analysis, cloud storage, and notifications and warnings to medical experts.
- Smart Agriculture System
- Explanation: To improve irrigation, and track soil moisture, humidity, and temperature, an IoT framework has to be deployed for smart agriculture.
- Mechanisms: Node-RED, Raspberry Pi/Arduino, sensors (temperature, soil moisture), AWS IoT Core, and Azure IoT Hub.
- Major Characteristics: Mobile application for tracking, automated irrigation control, gathering of sensor data, and cloud storage and analysis.
- IoT-Based Smart Parking System
- Explanation: A smart parking framework should be created with cloud services, which directs users to potential parking areas by identifying them.
- Mechanisms: MQTT, Raspberry Pi/Arduino, sensors (infrared, ultrasonic), Google Cloud IoT, and AWS IoT Core.
- Major Characteristics: Actual-time identification of parking area, mobile application for navigation, cloud-related data storage, and analytics for parking utilization.
- Industrial IoT Monitoring System
- Explanation: For predictive maintenance, we plan to track industrial machinery by developing a framework with cloud analytics and IoT sensors.
- Mechanisms: Python, MQTT, sensors (temperature, vibration), AWS IoT Analytics, and Azure IoT Hub.
- Major Characteristics: Cloud dashboards, machinery tracking, predictive maintenance alerts, and data analytics.
- Environmental Monitoring System
- Explanation: To monitor air quality, humidity levels, and temperature, an IoT-related ecological tracking framework must be deployed.
- Mechanisms: MQTT, Raspberry Pi/Arduino, sensors (humidity, temperature, air quality), Google Cloud IoT, and AWS IoT Core.
- Major Characteristics: Actual-time gathering of ecological data, alerts for threshold violations, cloud storage, and data visualization.
- Smart City Infrastructure Management
- Explanation: As a means to track and handle infrastructure like water supply, waste management, and street lighting, a smart city approach has to be created.
- Mechanisms: Node-RED, Raspberry Pi/Arduino, sensors (water flow, motion, light), AWS IoT Core, and Azure IoT Hub.
- Major Characteristics: Infrastructure tracking, data analytics, cloud-related control, and automated lighting and waste management.
- IoT-Based Fleet Management System
- Explanation: To track and handle vehicles, we aim to develop a fleet management framework with cloud services and IoT devices.
- Mechanisms: MQTT, Raspberry Pi/Arduino, GPS modules, Google Cloud IoT, and AWS IoT Core.
- Major Characteristics: Actual-time vehicle monitoring, maintenance notifications, fuel usage tracking, and route enhancement.
- Smart Building Energy Management
- Explanation: In buildings, track and handle energy usage by deploying an IoT framework with cloud-related analytics.
- Mechanisms: MQTT, Raspberry Pi/Arduino, energy meters, AWS IoT Core, and Azure IoT Hub.
- Major Characteristics: Energy tracking in actual-time, usage reports, automated energy-saving controls, and cloud storage and analysis.
- IoT-Based Smart Water Management System
- Explanation: Specifically in agricultural areas or homes, the water utilization must be observed and handled. For that, create a framework with cloud services and IoT sensors.
- Mechanisms: MQTT, Raspberry Pi/Arduino, water flow sensors, Google Cloud IoT, and AWS IoT Core.
- Major Characteristics: Actual-time water usage tracking, data analytics, automated irrigation, and leak identification alerts.
- IoT-Enabled Smart Grid Management
- Explanation: A smart grid framework should be developed, which can track and handle electricity usage and sharing by means of IoT devices.
- Mechanisms: Node-RED, Raspberry Pi/Arduino, smart meters, AWS IoT Core, and Azure IoT Hub.
- Major Characteristics: Tracking electricity usage in actual-time, fault identification, load balancing, and energy utilization analytics.
- IoT-Based Asset Tracking System
- Explanation: To track the condition and location of assets in actual-time, an asset monitoring framework has to be deployed, which utilizes IoT sensors.
- Mechanisms: MQTT, Raspberry Pi/Arduino, RFID tags, GPS modules, Google Cloud IoT, and AWS IoT Core.
- Major Characteristics: Actual-time asset monitoring, notifications for illicit activities, cloud storage, and usage analytics.
- IoT-Driven Predictive Maintenance for Smart Manufacturing
- Explanation: For manufacturing machinery, we intend to build a predictive maintenance framework by means of cloud analytics and IoT sensors.
- Mechanisms: Python, MQTT, sensors (temperature, vibration), AWS IoT Analytics, and Azure IoT Hub.
- Major Characteristics: Tracking of equipment health, cloud-related data analysis, predictive maintenance alerts, and maintenance planning.
- Smart Traffic Management System
- Explanation: A smart traffic management framework must be developed, which tracks and handles traffic flow by utilizing cloud analytics and IoT sensors.
- Mechanisms: MQTT, Raspberry Pi/Arduino, traffic sensors, cameras, Google Cloud IoT, and AWS IoT Core.
- Major Characteristics: Actual-time traffic monitoring, traffic pattern analysis, congestion identification, and automated traffic light regulation.
- IoT-Based Waste Management System
- Explanation: To track waste levels and improve gathering paths using IoT sensors, a waste management framework has to be deployed.
- Mechanisms: MQTT, raspberry Pi/Arduino, ultrasonic sensors, AWS IoT Core, and Azure IoT Hub.
- Major Characteristics: Waste level tracking in actual-time, notifications for full bins, path enhancement for waste gathering, and cloud-related data storage.
What are some ideas for a final project in cloud security?
As a means to develop a final project, an efficient and ideal topic must be selected in terms of individual expertise, requirements, and accessible materials. For a final project in cloud security, we recommend a few important plans that involve different factors of cloud platforms such as securing data, infrastructure, and applications:
- Data Encryption and Key Management in Cloud Storage
- Outline: For encrypting data that is stored in the cloud, an efficient framework has to be created. In a safer manner, it should handle the encryption keys.
- Important Characteristics: Access control strategies, secure key management approaches, and data encryption in both active and inactive state.
- Mechanisms: Python/Java, Azure Key Vault, Google Cloud KMS, and AWS KMS.
- Intrusion Detection System (IDS) for Cloud Environments
- Outline: To identify and react to security hazards in actual-time, an IDS must be developed for cloud platforms.
- Important Characteristics: Actual-time tracking, anomaly identification with machine learning, response techniques, and automated alerting.
- Mechanisms: Python, Kibana (ELK Stack), Logstash, Elasticsearch, Suricata, and AWS GuardDuty.
- Identity and Access Management (IAM) Framework
- Outline: As a means to handle access to cloud resources and user identities safely, an efficient IAM system should be modeled and deployed.
- Important Characteristics: Audit records, single sign-on (SSO), role-based access control (RBAC), and multi-factor authentication (MFA).
- Mechanisms: Python, Azure AD, OAuth, OpenID Connect, and AWS IAM.
- Secure Cloud Migration Strategy
- Outline: For transferring data and applications to the cloud in a safer manner, we plan to create an extensive policy.
- Important Characteristics: Adherence to rules, secure network architecture, data encryption while transmission, and risk evaluation.
- Mechanisms: Python, Terraform, Google Cloud Migrate, Azure Migrate, and AWS Migration Hub.
- Blockchain-Based Access Control System for Cloud Services
- Outline: To improve reliability and security, a decentralized access control framework has to be deployed by means of blockchain mechanisms.
- Important Characteristics: Secure data exchange, audit trails, smart contracts for access control, and decentralized identity management.
- Mechanisms: JavaScript/Python, Solidity, Hyperledger Fabric, and Ethereum.
- Zero Trust Security Model in Cloud Computing
- Outline: In a cloud platform, a zero trust security model must be investigated and applied. It is important to consider least privilege access and consistent verification.
- Important Characteristics: Actual-time threat identification, policy implementation, consistent authentication, and micro-segmentation.
- Mechanisms: Python/Go, Istio, Kubernetes, Azure Virtual Network, and AWS VPC.
- Cloud Security Posture Management (CSPM) Tool
- Outline: Particularly in cloud platforms, track and handle security setups in a constant manner by creating a CSPM tool.
- Important Characteristics: Compliance tracking, setup evaluation, risk identification, and remediation suggestions.
- Mechanisms: Python/JavaScript, Terraform, Azure Policy, and AWS Config.
- Privacy-Preserving Data Analytics in the Cloud
- Outline: In addition to securing confidential details, we intend to carry out data analytics in the cloud by applying privacy-preserving methods.
- Important Characteristics: Privacy-preserving machine learning, encrypted data processing, secure multi-party computation, and differential privacy.
- Mechanisms: Python, AWS SageMaker, TensorFlow Privacy, and PySyft.
- Automated Compliance Checking for Cloud Services
- Outline: Important security principles and rules must be followed by cloud services. To check this adherence in an automatic way, a robust framework has to be developed.
- Important Characteristics: Automated compliance reviews, compliance frameworks (for instance: HIPAA, GDPR), remediation ideas, and reporting tools.
- Mechanisms: Python/Java, Azure Security Center, and AWS Security Hub.
- Secure API Gateway for Cloud-Based Applications
- Outline: To secure and handle access to cloud-related applications, a safer API gateway should be modeled and deployed.
- Important Characteristics: Threat identification, logging and tracking, authentication and authorization, and API rate limiting.
- Mechanisms: Python/Node.js, JWT, OAuth, Kong, AWs API Gateway.
- Cloud-Based Disaster Recovery and Business Continuity Plan
- Outline: A disaster recovery strategy must be created. In the cloud, assure business endurance by applying a framework.
- Important Characteristics: Failover techniques, automated backups, high availability, and recovery testing.
- Mechanisms: Python/JavaScript, Google Cloud Disaster Recovery, Azure Site Recovery, and AWS Backup.
- Security Information and Event Management (SIEM) System for Cloud
- Outline: In a cloud platform, gather, examine, and react to security incidents through applying a SIEM framework.
- Important Characteristics: Actual-time event correlation, log aggregation, threat identification, and automated incident response.
- Mechanisms: Python/JavaScript, AWS CloudTrail, ELK Stack, and Splunk.
- Machine Learning for Threat Detection in Cloud Environments
- Outline: Specifically in cloud platforms, we aim to identify and react to security hazards by means of machine learning algorithms.
- Important Characteristics: Actual-time tracking, anomaly identification, automated threat response, and predictive analytics.
- Mechanisms: Python, Scikit-learn, TensorFlow, and AWS SageMaker.
- IoT Security in Cloud-Based Systems
- Outline: For handling IoT data and devices in cloud-related systems, an efficient security approach should be created.
- Important Characteristics: Data morality checks, intrusion detection, secure data sharing, and device authentication.
- Mechanisms: Python/Node.js, MQTT, Azure IoT Hub, and AWS IoT Core.
- Cloud Security Audit and Penetration Testing Framework
- Outline: On cloud platforms, plan to carry out penetration testing and security audits by developing a framework.
- Important Characteristics: Reporting tools, risk analysis, vulnerability evaluation, and automated scanning.
- Mechanisms: Python/Bash, AWS Inspector, Metasploit, and Kali Linux.
Relevant to the usage of cloud environments and IoT, we listed out numerous projects that are both fascinating and significant. Appropriate for a final project in cloud security, several compelling plans are proposed by us, along with concise outlines, important characteristics, and mechanisms.
Cloud Computing IOT Project Topics & Ideas
Cloud Computing IOT Project Topics & Ideas which you can apply in your research work are listed below, we have more than 15+ years of research experience so we give you tailored reasech support on your required areas of interest.
- Securing IoT networks in cloud computing environments: a real-time IDS
- An experimental study of fog and cloud computing in CEP-based Real-Time IoT applications
- Task partitioning and offloading in IoT cloud-edge collaborative computing framework: a survey
- Enhancement of an IoT hybrid intrusion detection system based on fog-to-cloud computing
- A cloud-edge collaborative computing framework using potential games for space-air-ground integrated IoT
- An IoT-based task scheduling optimization scheme considering the deadline and cost-aware scientific workflow for cloud computing
- Rotating behind security: an enhanced authentication protocol for IoT-enabled devices in distributed cloud computing architecture
- Exploration of police vocational training mode based on face recognition technology in the context of IoT cloud computing
- IoT based Social Device Network with Cloud Computing Architecture
- The Cloud based Edge Computing with IoT Infrastructure and Security
- Towards an Effective Management of IoT by Integrating Cloud and Fog Computing
- Electric charging station management using IoT and cloud computing framework for sustainable green transportation
- Hybrid approach for suspicious object surveillance using video clips and UAV images in cloud-IoT-based computing environment
- IoT workload offloading efficient intelligent transport system in federated ACNN integrated cooperated edge-cloud networks
- Cloud-Fog Trustworthy Computing for Information Sharing in Dynamic IoT System
- Heuristic-Based IoT Application Modules Placement in the Fog-Cloud Computing Environment
- Research on Problems, Challenges and Opportunities Based on Internet of Things (IoTs) and Cloud Computing
- IoT & Cloud Computing-based Remote Healthcare Monitoring System for an Elderly-Centered Care
- Current security and privacy issues, and concerns of Internet of Things (IoT) and Cloud Computing: A review
- An experimental study of fog and cloud computing in CEP-based Real-Time IoT applications
