Integrating IoT Sensors and Smart Automation into Traditional Sustainable Agriculture Practices

2026-10-27T11:47:20+00:00

Indian farming draws on generations of experience in maintaining soil, conserving water, choosing crop combinations, and managing pests through ecological methods. Much of this knowledge is shared within farming communities and applied through observation and judgement rather than continuous measurement. Low-cost Internet of Things (IoT) devices now make it possible to collect field data, send it over low-power networks, process it locally, and operate selected equipment automatically. This paper examines ways these capabilities can support traditional sustainable agriculture. It discusses practices including Zero Budget Natural Farming (ZBNF), mulching, mixed cropping, and rainwater harvesting, along with relevant sensors, communication options, analytics, and actuators. The proposed approach keeps farmers and their agronomic knowledge at the centre: IoT supplies measurements and timely feedback, while decisions remain open to farmer review. The paper also considers barriers such as equipment cost, calibration, maintenance, rural connectivity, energy supply, interoperability, digital literacy, and data ownership. Published quantitative evidence for IoT-assisted traditional farming remains limited, so potential benefits need to be tested through field studies rather than assumed.

Smart Movable Road Divider System for Traffic Flow Management and Emergency Path Clearance

2026-10-09T09:39:21+00:00

Rapid urbanization has intensified traffic congestion, leading to critical bottlenecks and prolonged travel times in modern metropolitan centers. Fixed lane boundaries fail to adapt to asymmetrical traffic flows during peak commuting hours, leaving lanes in one direction underutilized while opposing lanes experience severe gridlock. Furthermore, traffic congestion heavily delays emergency response vehicles, risking lives. This paper proposes a dynamic, cloud-integrated road divider framework driven by an ESP32 microcontroller and sensor arrays. By evaluating real-time vehicular density using proximity sensors and computer vision algorithms, the system dynamically repositions a movable road divider using motor-driven actuators to reallocate lane capacity based on demand. Additionally, real-time GPS tracking and visual cues prioritize emergency vehicles by automatically reconfiguring dividers to clear dedicated transit channels. System telemetry is continuously synchronized with an IoT cloud dashboard for central monitoring and manual overrides. Experimental prototype evaluation demonstrates that the proposed framework substantially improves lane utilization and reduces emergency clearance delay.

Journal of IoT-based Distributed Sensor Networks (e-ISSN: 3048-9202)

Integrating IoT Sensors and Smart Automation into Traditional Sustainable Agriculture Practices

Smart Movable Road Divider System for Traffic Flow Management and Emergency Path Clearance