A5045050884- Smart Agriculture and AI
- Advanced Sensor and Energy Harvesting Materials
- Analytical Chemistry and Sensors
- Greenhouse Technology and Climate Control
- Leaf Properties and Growth Measurement
- Low-power high-performance VLSI design
- Carbon Nanotubes in Composites
- Gas Sensing Nanomaterials and Sensors
- Neuroscience and Neural Engineering
- VLSI and Analog Circuit Testing
- Analog and Mixed-Signal Circuit Design
- VLSI and FPGA Design Techniques
- Surface Modification and Superhydrophobicity
- Remote Sensing in Agriculture
- Advanced Chemical Sensor Technologies
- 3D IC and TSV technologies
- ECG Monitoring and Analysis
- Mobile Crowdsensing and Crowdsourcing
- Peanut Plant Research Studies
- Radiation Effects in Electronics
- Physical Unclonable Functions (PUFs) and Hardware Security
- Advanced biosensing and bioanalysis techniques
- Conducting polymers and applications
- EEG and Brain-Computer Interfaces
- Human Mobility and Location-Based Analysis
Dhirubhai Ambani Institute of Information and Communication Technology
2020-2024
Plant diseases cause losses to agricultural production and hence, the economy. This necessitates a need develop prediction models for plant disease detection assessment. Fungal infection, most dominant disease, can be controlled by taking appropriate measures if detected at an early stage. The article aims expert system of various fungal (powdery mildew, anthracnose, rust, root rot/leaf blight). A multi-layered perceptron model is used classification which not only detects effectively but...
Early plant disease detection and providing the control measures have become highly desirable to improve crop yield. Leaf wetness duration (LWD) is one of essential parameters related development fungal on leaf canopy. To measured LWD, sensor (LWS) widely used. Commercially available LWS are made printed circuit board (PCB) technology, which has an operational issue during field deployment such as weight sensor, contact resistance between leaves, form factor most importantly, affordability....
Leaf wetness duration (LWD), soil moisture, temperature, ambient and relative humidity information are the essential factors that leads to germination of plant disease. In this work, an internet things (IoT) enabled leaf sensor (LWS) moisture (SMS) is developed. Subsequently, commercial temperature (ST), (RH) (AT) used for disease prediction. The developed LWS offers a response about 250% when exposed air water time 20 seconds attributes hysteresis ±3 %. Acrylic protective lacquer (APL)...
Plant disease detection and management is one of the pivotal areas in agriculture sector, which needs attention to abate crop loss. The recent trends machine learning deep have played a significant role reducing loss with help early plant detection. For prior information on soil moisture, ambient temperature, relative humidity, leaf wetness sensor (LWS), rainfall are crucial parameters. In this work, objective identify source canopy, can arise due irrigation, rainfall, or dew. To either...
One of the crucial variables for accurate irrigation models is soil moisture data. Recent advancement in microsensors has opened avenues to fabricate low-cost and highly sensitive sensors situ measurements. For these microsensors, sensing films play a pivotal role, considering selectivity sensitivity. In this work, we have explored Ti3C2Tx MXene two-dimensional (2D) nanomaterials as sensor's film. purpose, interdigitated electrodes (IDEs) been fabricated on silicon substrate using...
Groundnut cultivation faces persistent challenges from leaf spot disease, which affects crop yield and quality. This letter investigates the influence of environmental soil parameters on germination disease in groundnut plants where Internet Things (IoT)-enabled sensor system is used to collect data. A array consisting moisture, temperature, wetness (LWS), ambient humidity sensors are deployed monitor critical factors. The aforementioned collectively provide comprehensive insights into...
Disease detection and prevention in plants are crucial for generating healthy crops securing the livelihood of farmers. Leaf wetness duration (LWD), ambient temperature, relative humidity (RH) essential parameters that lead to germination fungal diseases plants. In this work, an in-house-developed leaf sensor (LWS) is used capture LWD, commercial temperature sensors record humidity, respectively. Subsequently, these interfaced with Internet Things (IoT)-enabled electronics deployed (three...
It is pivotal to monitor and examine the plant disease during in-situ measurements abate crop loss. For this purpose, leaf wetness sensors (LWS) are widely used. However, for LWS measurements, operational exposure always a concern considering growth at different stages. During stem angle changes even canopy bends either inwards or outward due environmental factors physical trauma. Thus, placed on may produce erroneous results. In work, we have examined effect of bending radius (outward...
To abate crop loss, it is important to explore the plant disease management systems, where leaf wetness sensors (LWS) are widely used. The duration (LWD) extracted from LWS related diseases. In this work, we have fabricated on polyamide flexible substrate Molybdenum disulfide (MoS <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) used as sensing film mechanism. Further, passivated MoS with help of acrylic protective lacquer (APL)...
At nanometer technology nodes, the efficient signal integrity and performance assessment of vast on-chip interconnects are crucial challenging. For a long time, copper (Cu) has been used as an interconnect material in integrated circuits (ICs). However, heading towards lower Cu is becoming inadequate to satisfy requirements for high-speed applications due its physical limitations. To mitigate this issue, multiwall carbon nanotube bundle (MWCNTB) proven be better replacement Cu. Hence,...
One of the driving factors leading to modernization in agriculture sector is era sensors-driven technologies. Annually, as reported by Associated Chambers Commerce and Industry India, $500 billion crops are lost due pests plant diseases a country like where at least 200 million Indians go bed hungry every night. For detection disease, measurement leaf wetness duration (LWD) values becomes crucial step. This requirement measuring LWD led development an situ IoT-enabled LW sensor earlier. The...
Due to technology scaling in deep submicron region, on-chip interconnects have become a major concerning issue for overall circuit performance. Therefore, it is necessary evaluate the performance of order predict output design. In this paper, back-propagation feed forward neural network (FFNN) technique employed prediction driver-interconnect-load (DIL) model. Levenberg-Marquardt (LM) algorithm used as training algorithm. The model provides faster when compared traditional analysis method....
A multitude of sensor models is being embedded in a variety smartphone brands. Notably, the accelerometer has been widely used to recognize human-induced activities leading growth human activity recognition (HAR) research. However, diversities create heterogeneity data which could result inaccurate accuracies. Existing empirical work handling diverse set mobile devices do not pay attention this issue. In paper, we report on bias observed across 13 different spanning 26 phones. continuous...