Krishi Integrated Command and Control Centre (ICCC)
Time to Read :🕑 11 Mins
Why in news?
Ministry of Agriculture & Farmers Welfare, inaugurated a Krishi Integrated Command and Control Centre (ICCC) at Krishi Bhavan in New Delhi. This ICCC acts as a big-screen dashboard showcasing all digital innovations in the agriculture sector.
.
What is the Krishi ICCC?
The ICCC is a tech-based solution involving multiple IT applications and platforms, which is designed to help in making informed decisions.
The centre is housed in the Ministry of Agriculture & Farmers’ Welfare, which is responsible for legislation, policy formation, and implementation of initiatives in the agriculture sector.
The ICCC uses state of the art technologies such as artificial intelligence, remote sensing, and Geographic Information Systems (GIS) to collect and process large amounts of granular data — on temperatures, rainfall, wind speed, crop yields and production estimations — and presents it in graphical format.
What is the objective of the ICCC?
The ICCC will enable comprehensive monitoring of the farm sector by making available at one place geospatial information received from multiple sources, including remote sensing.
Plot-level data received through soil survey.
Weather data from the India Meteorological Department (IMD).
Sowing data from Digital Crop Survey.
Farmer- and farm-related data from Krishi MApper, an application for geo-fencing and geo-tagging of land.
Market intelligence information from the Unified Portal for Agricultural Statistics (UPAg).
Yield estimation data from the General Crop Estimation Survey (GCES).
The integrated visualisation of the data will enable quick and efficient decision-making by the The ICCC ecosystem can be linked with the PM-Kisan chatbot going forward.
ICCC work process
On eight large, 55-inch LED screens installed at the ICCC, you can see information on crop yields, production, drought situation, cropping patterns (geographic region-wise and year-wise) in map, timeline, and drill-down views.
You can also see the relevant trends (periodic and non-periodic), outliers, and Key Performance Indicators (KPIs), and receive insights, alerts, and feedback on agriculture schemes, programmes, projects, and initiatives.
The ICCC uses platforms including the Krishi Decision Support System (DSS) to collect micro-level data, process it, and present the macro picture.
The ICCC has a contact centre and a helpdesk facility, with the operator’s handset capable of being converted into a call centre. If needed, farmer beneficiaries can interact directly with officials or the Minister through video conferencing facilities.
Applications of ICCC
Farmer's Advisory: The ICCC allows visualisation of GIS based soil carbon mapping as well as soil health card data for a particular district together at one place. “This, when visualised with weather-related data from IMD for the selected district, will allow a customised and authentic advisory to be sent to the farmer about the type of crops that can be grown, and water and fertiliser requirements,” an official said.
Drought Actions: According to officials, increase or decrease in yield from a specific region (as per GCES data) can be correlated with weather, rainfall, and other information visualised through the Drought Portal, enabling the administration to understand the reason for increase/ decrease in yield and to take decisions proactively.
Crop Diversification: An analysis of crop diversification maps, together with field variability for paddy, will enable decision-makers to identify regions with scope for diversified cropping, so that farmers can be advised accordingly.
Farm Data Repository: Krishi Decision Support System (K-DSS), a platform under development, will act as an agriculture data repository. Integrated spatial and non-spatial data will be superimposed as a layer on the GIS map, and various AI/ ML models would be run on the data. The K-DSS will help in evidence-based, efficient, and data-driven decision-making, and assist in preparing customised advisories for farmers.
Validation of Yield: Yield as captured through Krishi MApper can be analysed with the yield generated through GCES application for a plot.
Way forward
The ICCC can create an ecosystem based on which individual farmer-level advisories can be generated through apps like Kisan e-mitra, a chatbot developed for PM-Kisan beneficiaries.
The AI-/ machine learning-based system will identify a farmer through his/ her mobile number or Aadhaar, and match it with the farmer’s field information obtain through land records, historical crop sowing information from the crop registry, weather data from IMD, etc.
It will then generate a customised advisory in the local language of the farmer.
For this, the system will use the Bhashini platform that allows translation into several Indian languages.
The need to curb black carbon emissions
Time to Read :🕑 11 Mins
Why in news?
According to the Ministry of New and Renewable Energy, India had installed a renewable energy capacity of over 180 GW by 2023 and is expected to meet its target of 500 GW by 2030.
Background
At the COP26 climate talks in Glasgow in November 2021, India pledged to achieve net-zero emissions by 2070, positioning itself as a frontrunner in the race to carbon neutrality.
While carbon dioxide mitigation strategies will yield benefits in the long term, they need to go hand-in-hand with efforts that provide short-term relief.
Why is black carbon relevant?
Black carbon is the dark, sooty material emitted alongside other pollutants when biomass and fossil fuels are not fully combusted.
It contributes to global warming and poses severe risks.
Studies have found a direct link between exposure to black carbon and a higher risk of heart disease, birth complications, and premature death.
Most black carbon emissions in India arise from burning biomass, such as cow dung or straw, in traditional cookstoves.
According to a 2016 study, the residential sector contributes 47% of India’s total black carbon emissions.
Industries contribute a further 22%, diesel vehicles 17%, open burning 12%, and other sources 2%.
Decarbonisation efforts in the industry and transport sectors in the past decade have yielded reductions in black carbon emissions, but the residential sector remains a challenge.
PMUY status
In May 2016, the Government of India said the Pradhan Mantri Ujjwala Yojana (PMUY) would provide free liquefied petroleum gas (LPG) connections to households below the poverty line.
The primary objective was to make clean cooking fuel available to rural and poor households and reduce their dependence on traditional cooking fuels.
The PMUY has established infrastructure to go with LPG connections, including free gas stoves, deposits for LPG cylinders, and a distribution network.
The programme has thus, been able to play a vital role in reducing black carbon emissions, as it offers a cleaner alternative to traditional fuel consumption.
The programme has provided connections to over 10 crore households as of January 2024.
PMAU - refill and uses cahllanges
In 2022-2023, 25% of all PMUY beneficiaries — 2.69 crore people — availed either zero LPG refill or only one LPG refill, according to RTI data, meaning they still relied entirely on traditional biomass for cooking.
In August 2023, the average PMUY beneficiary household consumes only 3.5-4 LPG cylinders per year instead of the six or seven a regular non-PMUY household uses.
This means up to half of all the energy needs of a PMUY beneficiary household are still met by traditional fuels, which have high black carbon emissions.
A shortage of LPG and higher usage of traditional fuels also affect women and children disproportionately.
They are more prone to higher levels of indoor air pollution, causing many health issues and leading to premature deaths.
What is the government’s role?
The key to enhancing the quality of life in these areas lies primarily in securing access to clean cooking fuels.
While the future holds the promise of meeting energy needs in rural areas through renewable sources, the immediate benefits for rural communities are poised to come from using LPG.
In October 2023, the government increased the LPG subsidy to ₹300 from ₹200.
But with rapid increase in LPG prices over the last five years, the cost of a 14.2-kg LPG cylinder, even with an additional subsidy, is still about ₹600 per cylinder.
Most PMUY beneficiaries find the price too high, more so since cow dung, firewood, etc. are ‘free’ alternatives.
PM announced a further price reduction of ₹100 in March 2024, but this subsidy is expected to be temporary.
The government has estimated that about ₹12,000 crore will be spent on PMUY subsidies in 2024-2025, a figure that has continuously increased each year since the scheme’s inception.
While it is the rightful duty of the government to make clean fuel affordable through subsidies, the problem of low refill rates will persist if availability issues are not addressed.
Another big hurdle to the PMUY’s success is the lack of last-mile connectivity in the LPG distribution network, resulting in remote rural areas depending mostly on biomass.
One potential solution to this issue is the local production of coal-bed methane (CBM) gas by composting biomass.
CBM is a much cleaner fuel with lower black-carbon emissions and investment.
Panchayats can take the initiative to produce CBM gas locally at the village level, ensuring every rural household can access clean cooking fuel.
Global best practices
As India navigates its responsibilities on the global stage towards long-term decarbonisation, there is an urgent need to act.
Prioritising black carbon reduction through initiatives such as the PMUY scheme can help India become a global leader in addressing regional health concerns and help meet its Sustainability Development Goal of providing affordable clean energy to everyone and contributing to global climate mitigation.
Recent estimates have indicated that mitigating residential emissions will avoid more than 6.1 lakh deaths per year from indoor exposure to air pollution.
80% of CPCB green funds unused: NGT
Time to Read :🕑 5 Mins
Why in news?
According to a report submitted by the Central Pollution Control Board to the National Green Tribunal, as much as 80% of the environment protection charge (EPC) and environmental compensation (EC) collected remains unspent.
About
As of January 3, 2024, the CPCB had collected Rs 383.39 crore in the EPC account and disbursed Rs 95.4 crore, leaving a balance of Rs 288.49 crore.
CPCB stated that Rs 88.7 crore was spent on works such as commissioning of scientific studies, inspection drives and clean air campaign.
Furthermore, CPCB spent Rs 61.13 crore, out of Rs 393.8 crore, from the environment compensation (EC) pool of funds meant for mitigation of air quality in different cities, environmental remediation and ground surveys.
The Central Pollution Control Board (CPCB)
The Central Pollution Control Board (CPCB), statutory organisation, was constituted in September, 1974 under the Water (Prevention and Control of Pollution) Act, 1974. Further, CPCB was entrusted with the powers and functions under the Air (Prevention and Control of Pollution) Act, 1981.
The Central Pollution Control Board is fully funded by the Central Ministry of Environment & Forests.
The State Pollution Control Boards receive funds from the concerned State Governments and from the Central Ministry of Environment & Forests through reimbursement of Water Cess (upto 80%) collected by the respective State Boards.
In addition, the State Boards receive fees for processing for applications from the industries for issuing consent in regard to discharge of effluent and emissions.
SPCBs are getting only marginal/ nominal financial assistance from State Governments.
In some of the State Pollution Control Boards, State Governments are not providing budgetary grants.
State Pollution Control Boards are dependent on consent and authorization fee and cess reimbursements which they get out of cess collections.
India Employment Report 2024
Time to Read :🕑 7 Mins
Why in news?
Recently, the ‘India Employment Report 2024’ released by the Institute for Human Development (IHD) and International Labour Organisation (ILO).
Key Finding
According to report, even as overall labour force participation, workforce participation and employment rates improved in India in recent years after showing long-term deterioration during 2000-2019, the employment conditions remain poor.
The slow transition to non-farm employment has reversed.
Women largely account for the increase in self-employment and unpaid family work.
Youth employment is of poorer quality than employment for adults, with a higher proportion of unpaid family work among youth than adults along with stagnant or declining wages and earnings.
The IHD-ILO report noted that youth employment and underemployment increased between 2000 and 2019 but declined during the pandemic years.
However, unemployment among youths, especially those with a secondary level of education or higher, has intensified over time.
In 2022, the share of unemployed youths in the total unemployed population was 82.9 per cent.
The share of educated youths among all unemployed people also increased, from 54.2 per cent in 2000 to 65.7 per cent in 2022.
Among the educated (secondary level or higher) unemployed youths, women accounted for a larger share (76.7 per cent) than men (62.2 per cent).
This indicates that the problem of unemployment in India has become increasingly concentrated among the youth, especially educated youths and women in urban areas.
Key recommandation
Economic policies are required to boost productive non-farm employment, especially in the manufacturing sector, with India likely to add 7-8 million youths annually to the labour force during the next decade or so.
India needs to give primacy to labour-intensive manufacturing employment to absorb the abundant unskilled labour and also to combine with select services.
More support needs to be provided to micro, small and medium-sized enterprises, especially by providing a more supportive, decentralised approach including digitalisation and artificial intelligence and a cluster-based approach to manufacturing.
India needs to improve the quality of jobs by investing in and regulating sectors that are likely to be an important source of employment for young people, such as the care sector, digital economy.
With a higher rate of urbanisation and migration expected in India, an inclusive urban policy is required to address the needs of migrants, women and impoverished young people.
Skills development and active labour market policies (ALMPs) need a more effective role in bridging the supply-demand gap in jobs and in making the overall labour market more inclusive.
Adding that a larger and more targeted role for state governments and stronger partnerships with the private sector and other stakeholders is also needed, along with greater contribution by the private and non-state sector.
The report highlighted five key policy areas for further action:
Promoting job creation
Improving employment quality
Addressing labour market inequalities
Strengthening skills and active labour market policies.
Bridging the knowledge deficits on labour market patterns and youth employment.
Can AI help in navigating mental health?
Time to Read :🕑 11 Mins
Why in news?
Sophisticated AI-enabled strategies can support clinicians in delivering both more accurate diagnoses and promoting person-centered treatments.
Background
Natural language processing (NLP), a branch of Artificial Intelligence (AI), enables computers to understand and interpret human language that mirrors human comprehension.
In mental healthcare, we are already seeing a rapid evolution of use cases for AI with affordable access to therapy and better support for clinicians.
AI help patients
External and internalised stigma persists across demographics and countries. Through text-based platforms and virtual mental health assistants, NLP programs provide privacy and anonymity that can improve help-seeking behaviour. For users, the chatbot can support them in reframing thoughts, validating emotions and providing personalised care, especially in the absence of human support.
Not only is this beneficial when a therapist is not accessible, but it also helps improve patient health outcomes just as well as in-person care.
Mental health treatment requires continuity of care to take a more holistic approach and reduce instances of relapse. For example, digital therapy assistants can help point you to resources for healthier coping in instances of distress, grief, and anxiety.
Since these chatbots are scalable, cost-effective, and available 24x7, they could therefore be integrated into existing health programs.
Additionally, companies building chatbots must proactively expand the scope of service delivery through partnerships and collaborations for follow-up services such as referrals, in-person treatment, or hospital care, where needed.
Challanges of AI
Data Privacy and Security: The collection and analysis of sensitive mental health data raise concerns about data privacy and security.
Accuracy and Bias: AI algorithms are only as accurate as the data they are trained on. Bias in training data can result in inaccurate predictions and reinforce existing disparities in mental health care.
Lack of Human Connection: While AI can provide valuable support, it cannot replace the human connection that is often essential in mental health care.
Misdiagnosis and False Positives: AI-driven systems may generate false positives or misdiagnosed mental health conditions, leading to unnecessary stress and interventions.
Ethical Dilemmas in Treatment Decisions: AI’s ability to recommend treatments raises ethical questions about who holds responsibility for treatment decisions.
AI help clinicians
Mental health illnesses have complex causes of origin, making it difficult to design a straightforward protocol or make a quick and accurate diagnosis. By using vast datasets, AI tools can help summarise information including clinical notes, patient conversations, neuroimages, and genetic information. This can help clinicians get up to speed with the entire patient history, saving valuable time during sessions.
Recent advancements in NLP programs have demonstrated the ability to forecast responses to antidepressants and antipsychotic drugs by analysing brain electrical activity, neuroimages, and clinical surveys.
Such predictive capability can streamline treatment decisions and minimise the risk of ineffective interventions.
Some chatbots are also creating e-triaging systems that can significantly reduce wait time and free up valuable clinical person-hours.
With improving bandwidth, mental health providers can devote a higher proportion of time to severe mental illnesses, such as bipolar disorder and schizophrenia, where specialised care is required.
Way forward
Companies must refine these applications by using more diverse population-wide datasets to minimise bias.
These programs can also incorporate a wider set of health indicators for a comprehensive patient care experience.
We expect greater success of these programs if they are guided by a conceptual framework for improving health outcomes and rigorously and continuously tested.
In the pursuit of innovation, governments and institutions need to prioritise user safety and well-being by ensuring adherence to global compliance standards. As these applications evolve, we must persist in updating our beliefs, governing laws and regulations, and demanding better standards of care.
Profile
Settings
Refer your friends
Sign out
